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Upload folder using huggingface_hub

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+ tekken.json filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
README.md CHANGED
@@ -1,5 +1,4 @@
1
  ---
2
- library_name: vllm
3
  language:
4
  - en
5
  - fr
@@ -26,17 +25,17 @@ language:
26
  - hi
27
  - bn
28
  license: apache-2.0
 
29
  inference: false
30
  base_model:
31
- - mistralai/Mistral-Small-3.1-24B-Instruct-2503
32
  extra_gated_description: >-
33
  If you want to learn more about how we process your personal data, please read
34
  our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
35
- tags:
36
- - mistral-common
37
  ---
38
 
39
- # Devstral Small 1.0
40
 
41
  Devstral is an agentic LLM for software engineering tasks built under a collaboration between [Mistral AI](https://mistral.ai/) and [All Hands AI](https://www.all-hands.dev/) 🙌. Devstral excels at using tools to explore codebases, editing multiple files and power software engineering agents. The model achieves remarkable performance on SWE-bench which positionates it as the #1 open source model on this [benchmark](#benchmark-results).
42
 
@@ -103,20 +102,41 @@ docker run -it --rm --pull=always \
103
 
104
  ### Local inference
105
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
106
  The model can also be deployed with the following libraries:
 
107
  - [`vllm (recommended)`](https://github.com/vllm-project/vllm): See [here](#vllm-recommended)
108
  - [`mistral-inference`](https://github.com/mistralai/mistral-inference): See [here](#mistral-inference)
109
  - [`transformers`](https://github.com/huggingface/transformers): See [here](#transformers)
110
- - [`LMStudio`](https://lmstudio.ai/): See [here](#lmstudio)
111
- - [`llama.cpp`](https://github.com/ggml-org/llama.cpp): See [here](#llama.cpp)
112
  - [`ollama`](https://github.com/ollama/ollama): See [here](#ollama)
113
 
114
 
115
  ### OpenHands (recommended)
116
 
117
- #### Launch a server to deploy Devstral Small 1.0
118
 
119
- Make sure you launched an OpenAI-compatible server such as vLLM or Ollama as described above. Then, you can use OpenHands to interact with `Devstral Small 1.0`.
120
 
121
  In the case of the tutorial we spineed up a vLLM server running the command:
122
  ```bash
@@ -198,6 +218,43 @@ Enjoy building with Devstral Small and OpenHands!
198
  </details>
199
 
200
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
201
  ### vLLM (recommended)
202
 
203
  We recommend using this model with the [vLLM library](https://github.com/vllm-project/vllm)
@@ -271,6 +328,7 @@ response = requests.post(url, headers=headers, data=json.dumps(data))
271
  print(response.json()["choices"][0]["message"]["content"])
272
  ```
273
 
 
274
  ### Mistral-inference
275
 
276
  We recommend using mistral-inference to quickly try out / "vibe-check" Devstral.
@@ -305,6 +363,14 @@ mistral-chat $HOME/mistral_models/Devstral --instruct --max_tokens 300
305
 
306
  You can then prompt it with anything you'd like.
307
 
 
 
 
 
 
 
 
 
308
  ### Transformers
309
 
310
  To make the best use of our model with transformers make sure to have [installed](https://github.com/mistralai/mistral-common) ` mistral-common >= 1.5.5` to use our tokenizer.
@@ -323,6 +389,7 @@ from mistral_common.protocol.instruct.messages import (
323
  )
324
  from mistral_common.protocol.instruct.request import ChatCompletionRequest
325
  from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
 
326
  from huggingface_hub import hf_hub_download
327
  from transformers import AutoModelForCausalLM
328
 
@@ -356,93 +423,4 @@ output = model.generate(
356
 
357
  decoded_output = tokenizer.decode(output[len(tokenized.tokens):])
358
  print(decoded_output)
359
- ```
360
-
361
- ### LMStudio
362
- Download the weights from huggingface:
363
-
364
- ```
365
- pip install -U "huggingface_hub[cli]"
366
- huggingface-cli download \
367
- "mistralai/Devstral-Small-2505_gguf" \
368
- --include "devstralQ4_K_M.gguf" \
369
- --local-dir "mistralai/Devstral-Small-2505_gguf/"
370
- ```
371
-
372
- You can serve the model locally with [LMStudio](https://lmstudio.ai/).
373
- * Download [LM Studio](https://lmstudio.ai/) and install it
374
- * Install `lms cli ~/.lmstudio/bin/lms bootstrap`
375
- * In a bash terminal, run `lms import devstralQ4_K_M.gguf` in the directory where you've downloaded the model checkpoint (e.g. `mistralai/Devstral-Small-2505_gguf`)
376
- * Open the LMStudio application, click the terminal icon to get into the developer tab. Click select a model to load and select Devstral Q4 K M. Toggle the status button to start the model, in setting toggle Serve on Local Network to be on.
377
- * On the right tab, you will see an API identifier which should be devstralq4_k_m and an api address under API Usage. Keep note of this address, we will use it in the next step.
378
-
379
- Launch Openhands
380
- You can now interact with the model served from LM Studio with openhands. Start the openhands server with the docker
381
-
382
- ```bash
383
- docker pull docker.all-hands.dev/all-hands-ai/runtime:0.38-nikolaik
384
- docker run -it --rm --pull=always \
385
- -e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.38-nikolaik \
386
- -e LOG_ALL_EVENTS=true \
387
- -v /var/run/docker.sock:/var/run/docker.sock \
388
- -v ~/.openhands-state:/.openhands-state \
389
- -p 3000:3000 \
390
- --add-host host.docker.internal:host-gateway \
391
- --name openhands-app \
392
- docker.all-hands.dev/all-hands-ai/openhands:0.38
393
- ```
394
-
395
- Click “see advanced setting” on the second line.
396
- In the new tab, toggle advanced to on. Set the custom model to be mistral/devstralq4_k_m and Base URL the api address we get from the last step in LM Studio. Set API Key to dummy. Click save changes.
397
-
398
- ### llama.cpp
399
-
400
- Download the weights from huggingface:
401
-
402
- ```
403
- pip install -U "huggingface_hub[cli]"
404
- huggingface-cli download \
405
- "mistralai/Devstral-Small-2505_gguf" \
406
- --include "devstralQ4_K_M.gguf" \
407
- --local-dir "mistralai/Devstral-Small-2505_gguf/"
408
- ```
409
-
410
- Then run Devstral using the llama.cpp CLI.
411
-
412
- ```bash
413
- ./llama-cli -m Devstral-Small-2505_gguf/devstralQ4_K_M.gguf -cnv
414
- ```
415
-
416
- ### Ollama
417
-
418
- You can run Devstral using the [Ollama](https://ollama.ai/) CLI.
419
-
420
- ```bash
421
- ollama run devstral
422
- ```
423
-
424
- ### Example: Understanding Test Coverage of Mistral Common
425
-
426
- We can start the OpenHands scaffold and link it to a repo to analyze test coverage and identify badly covered files.
427
- Here we start with our public `mistral-common` repo.
428
-
429
-
430
- After the repo is mounted in the workspace, we give the following instruction
431
- ```
432
- Check the test coverage of the repo and then create a visualization of test coverage. Try plotting a few different types of graphs and save them to a png.
433
- ```
434
- The agent will first browse the code base to check test configuration and structure.
435
-
436
- ![Repo Exploration](assets/images_example/example_mistral_common_1.png)
437
-
438
- Then it sets up the testing dependencies and launches the coverage test:
439
-
440
- ![Repo Exploration](assets/images_example/example_mistral_common_2.png)
441
-
442
- Finally, the agent writes necessary code to visualize the coverage.
443
- ![Repo Exploration](assets/images_example/example_mistral_common_3.png)
444
-
445
- At the end of the run, the following plots are produced:
446
- ![Repo Exploration](assets/images_example/example_mistral_common_res_1.png)
447
- ![Repo Exploration](assets/images_example/example_mistral_common_res_2.png)
448
- ![Repo Exploration](assets/images_example/example_mistral_common_res_3.png)
 
1
  ---
 
2
  language:
3
  - en
4
  - fr
 
25
  - hi
26
  - bn
27
  license: apache-2.0
28
+ library_name: vllm
29
  inference: false
30
  base_model:
31
+ - mistralai/Devstral-Small-2505
32
  extra_gated_description: >-
33
  If you want to learn more about how we process your personal data, please read
34
  our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
35
+ pipeline_tag: text2text-generation
 
36
  ---
37
 
38
+ # Model Card for mistralai/Devstrall-Small-2505
39
 
40
  Devstral is an agentic LLM for software engineering tasks built under a collaboration between [Mistral AI](https://mistral.ai/) and [All Hands AI](https://www.all-hands.dev/) 🙌. Devstral excels at using tools to explore codebases, editing multiple files and power software engineering agents. The model achieves remarkable performance on SWE-bench which positionates it as the #1 open source model on this [benchmark](#benchmark-results).
41
 
 
102
 
103
  ### Local inference
104
 
105
+ You can also run the model locally. It can be done with LMStudio or other providers listed below.
106
+
107
+ Launch Openhands
108
+ You can now interact with the model served from LM Studio with openhands. Start the openhands server with the docker
109
+
110
+ ```bash
111
+ docker pull docker.all-hands.dev/all-hands-ai/runtime:0.38-nikolaik
112
+ docker run -it --rm --pull=always \
113
+ -e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.38-nikolaik \
114
+ -e LOG_ALL_EVENTS=true \
115
+ -v /var/run/docker.sock:/var/run/docker.sock \
116
+ -v ~/.openhands-state:/.openhands-state \
117
+ -p 3000:3000 \
118
+ --add-host host.docker.internal:host-gateway \
119
+ --name openhands-app \
120
+ docker.all-hands.dev/all-hands-ai/openhands:0.38
121
+ ```
122
+
123
+ The server will start at http://0.0.0.0:3000. Open it in your browser and you will see a tab AI Provider Configuration.
124
+ Now you can start a new conversation with the agent by clicking on the plus sign on the left bar.
125
+
126
+
127
  The model can also be deployed with the following libraries:
128
+ - [`LMStudio (recommended for quantized model)`](https://lmstudio.ai/): See [here](#lmstudio-recommended-for-quantized-model)
129
  - [`vllm (recommended)`](https://github.com/vllm-project/vllm): See [here](#vllm-recommended)
130
  - [`mistral-inference`](https://github.com/mistralai/mistral-inference): See [here](#mistral-inference)
131
  - [`transformers`](https://github.com/huggingface/transformers): See [here](#transformers)
 
 
132
  - [`ollama`](https://github.com/ollama/ollama): See [here](#ollama)
133
 
134
 
135
  ### OpenHands (recommended)
136
 
137
+ #### Launch a server to deploy Devstral-Small-2505
138
 
139
+ Make sure you launched an OpenAI-compatible server such as vLLM or Ollama as described above. Then, you can use OpenHands to interact with `Devstral-Small-2505`.
140
 
141
  In the case of the tutorial we spineed up a vLLM server running the command:
142
  ```bash
 
218
  </details>
219
 
220
 
221
+ ### LMStudio (recommended for quantized model)
222
+ Download the weights from huggingface:
223
+
224
+ ```
225
+ pip install -U "huggingface_hub[cli]"
226
+ huggingface-cli download \
227
+ "mistralai/Devstral-Small-2505_gguf" \
228
+ --include "devstralQ4_K_M.gguf" \
229
+ --local-dir "mistralai/Devstral-Small-2505_gguf/"
230
+ ```
231
+
232
+ You can serve the model locally with [LMStudio](https://lmstudio.ai/).
233
+ * Download [LM Studio](https://lmstudio.ai/) and install it
234
+ * Install `lms cli ~/.lmstudio/bin/lms bootstrap`
235
+ * In a bash terminal, run `lms import devstralQ4_K_M.ggu` in the directory where you've downloaded the model checkpoint (e.g. `mistralai/Devstral-Small-2505_gguf`)
236
+ * Open the LMStudio application, click the terminal icon to get into the developer tab. Click select a model to load and select Devstral Q4 K M. Toggle the status button to start the model, in setting oggle Serve on Local Network to be on.
237
+ * On the right tab, you will see an API identifier which should be devstralq4_k_m and an api address under API Usage. Keep note of this address, we will use it in the next step.
238
+
239
+ Launch Openhands
240
+ You can now interact with the model served from LM Studio with openhands. Start the openhands server with the docker
241
+
242
+ ```bash
243
+ docker pull docker.all-hands.dev/all-hands-ai/runtime:0.38-nikolaik
244
+ docker run -it --rm --pull=always \
245
+ -e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.38-nikolaik \
246
+ -e LOG_ALL_EVENTS=true \
247
+ -v /var/run/docker.sock:/var/run/docker.sock \
248
+ -v ~/.openhands-state:/.openhands-state \
249
+ -p 3000:3000 \
250
+ --add-host host.docker.internal:host-gateway \
251
+ --name openhands-app \
252
+ docker.all-hands.dev/all-hands-ai/openhands:0.38
253
+ ```
254
+
255
+ Click “see advanced setting” on the second line.
256
+ In the new tab, toggle advanced to on. Set the custom model to be mistral/devstralq4_k_m and Base URL the api address we get from the last step in LM Studio. Set API Key to dummy. Click save changes.
257
+
258
  ### vLLM (recommended)
259
 
260
  We recommend using this model with the [vLLM library](https://github.com/vllm-project/vllm)
 
328
  print(response.json()["choices"][0]["message"]["content"])
329
  ```
330
 
331
+
332
  ### Mistral-inference
333
 
334
  We recommend using mistral-inference to quickly try out / "vibe-check" Devstral.
 
363
 
364
  You can then prompt it with anything you'd like.
365
 
366
+ ### Ollama
367
+
368
+ You can run Devstral using the [Ollama](https://ollama.ai/) CLI.
369
+
370
+ ```bash
371
+ ollama run devstral
372
+ ```
373
+
374
  ### Transformers
375
 
376
  To make the best use of our model with transformers make sure to have [installed](https://github.com/mistralai/mistral-common) ` mistral-common >= 1.5.5` to use our tokenizer.
 
389
  )
390
  from mistral_common.protocol.instruct.request import ChatCompletionRequest
391
  from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
392
+ from mistral_common.tokens.tokenizers.tekken import SpecialTokenPolicy
393
  from huggingface_hub import hf_hub_download
394
  from transformers import AutoModelForCausalLM
395
 
 
423
 
424
  decoded_output = tokenizer.decode(output[len(tokenized.tokens):])
425
  print(decoded_output)
426
+ ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
chat_template.jinja ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{- bos_token }}
2
+
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {%- if messages[0]['content'] is string %}
5
+ {%- set system_message = messages[0]['content'] %}
6
+ {%- else %}
7
+ {%- set system_message = messages[0]['content'][0]['text'] %}
8
+ {%- endif %}
9
+ {%- set loop_messages = messages[1:] %}
10
+ {%- else %}
11
+ {%- set system_message = "You are Devstral, a helpful agentic model trained by Mistral AI and using the OpenHands scaffold. You can interact with a computer to solve tasks.\n\n<ROLE>\nYour primary role is to assist users by executing commands, modifying code, and solving technical problems effectively. You should be thorough, methodical, and prioritize quality over speed.\n* If the user asks a question, like \"why is X happening\", don't try to fix the problem. Just give an answer to the question.\n</ROLE>\n\n<EFFICIENCY>\n* Each action you take is somewhat expensive. Wherever possible, combine multiple actions into a single action, e.g. combine multiple bash commands into one, using sed and grep to edit/view multiple files at once.\n* When exploring the codebase, use efficient tools like find, grep, and git commands with appropriate filters to minimize unnecessary operations.\n</EFFICIENCY>\n\n<FILE_SYSTEM_GUIDELINES>\n* When a user provides a file path, do NOT assume it's relative to the current working directory. First explore the file system to locate the file before working on it.\n* If asked to edit a file, edit the file directly, rather than creating a new file with a different filename.\n* For global search-and-replace operations, consider using `sed` instead of opening file editors multiple times.\n</FILE_SYSTEM_GUIDELINES>\n\n<CODE_QUALITY>\n* Write clean, efficient code with minimal comments. Avoid redundancy in comments: Do not repeat information that can be easily inferred from the code itself.\n* When implementing solutions, focus on making the minimal changes needed to solve the problem.\n* Before implementing any changes, first thoroughly understand the codebase through exploration.\n* If you are adding a lot of code to a function or file, consider splitting the function or file into smaller pieces when appropriate.\n</CODE_QUALITY>\n\n<VERSION_CONTROL>\n* When configuring git credentials, use \"openhands\" as the user.name and \"[email protected]\" as the user.email by default, unless explicitly instructed otherwise.\n* Exercise caution with git operations. Do NOT make potentially dangerous changes (e.g., pushing to main, deleting repositories) unless explicitly asked to do so.\n* When committing changes, use `git status` to see all modified files, and stage all files necessary for the commit. Use `git commit -a` whenever possible.\n* Do NOT commit files that typically shouldn't go into version control (e.g., node_modules/, .env files, build directories, cache files, large binaries) unless explicitly instructed by the user.\n* If unsure about committing certain files, check for the presence of .gitignore files or ask the user for clarification.\n</VERSION_CONTROL>\n\n<PULL_REQUESTS>\n* When creating pull requests, create only ONE per session/issue unless explicitly instructed otherwise.\n* When working with an existing PR, update it with new commits rather than creating additional PRs for the same issue.\n* When updating a PR, preserve the original PR title and purpose, updating description only when necessary.\n</PULL_REQUESTS>\n\n<PROBLEM_SOLVING_WORKFLOW>\n1. EXPLORATION: Thoroughly explore relevant files and understand the context before proposing solutions\n2. ANALYSIS: Consider multiple approaches and select the most promising one\n3. TESTING:\n * For bug fixes: Create tests to verify issues before implementing fixes\n * For new features: Consider test-driven development when appropriate\n * If the repository lacks testing infrastructure and implementing tests would require extensive setup, consult with the user before investing time in building testing infrastructure\n * If the environment is not set up to run tests, consult with the user first before investing time to install all dependencies\n4. IMPLEMENTATION: Make focused, minimal changes to address the problem\n5. VERIFICATION: If the environment is set up to run tests, test your implementation thoroughly, including edge cases. If the environment is not set up to run tests, consult with the user first before investing time to run tests.\n</PROBLEM_SOLVING_WORKFLOW>\n\n<SECURITY>\n* Only use GITHUB_TOKEN and other credentials in ways the user has explicitly requested and would expect.\n* Use APIs to work with GitHub or other platforms, unless the user asks otherwise or your task requires browsing.\n</SECURITY>\n\n<ENVIRONMENT_SETUP>\n* When user asks you to run an application, don't stop if the application is not installed. Instead, please install the application and run the command again.\n* If you encounter missing dependencies:\n 1. First, look around in the repository for existing dependency files (requirements.txt, pyproject.toml, package.json, Gemfile, etc.)\n 2. If dependency files exist, use them to install all dependencies at once (e.g., `pip install -r requirements.txt`, `npm install`, etc.)\n 3. Only install individual packages directly if no dependency files are found or if only specific packages are needed\n* Similarly, if you encounter missing dependencies for essential tools requested by the user, install them when possible.\n</ENVIRONMENT_SETUP>\n\n<TROUBLESHOOTING>\n* If you've made repeated attempts to solve a problem but tests still fail or the user reports it's still broken:\n 1. Step back and reflect on 5-7 different possible sources of the problem\n 2. Assess the likelihood of each possible cause\n 3. Methodically address the most likely causes, starting with the highest probability\n 4. Document your reasoning process\n* When you run into any major issue while executing a plan from the user, please don't try to directly work around it. Instead, propose a new plan and confirm with the user before proceeding.\n</TROUBLESHOOTING>" %}
12
+ {%- set loop_messages = messages %}
13
+ {%- endif %}
14
+ {{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}
15
+
16
+ {%- for message in loop_messages %}
17
+ {%- if message['role'] == 'user' %}
18
+ {%- if message['content'] is string %}
19
+ {{- '[INST]' + message['content'] + '[/INST]' }}
20
+ {%- else %}
21
+ {{- '[INST]' }}
22
+ {%- for block in message['content'] %}
23
+ {%- if block['type'] == 'text' %}
24
+ {{- block['text'] }}
25
+ {%- elif block['type'] in ['image', 'image_url'] %}
26
+ {{- '[IMG]' }}
27
+ {%- else %}
28
+ {{- raise_exception('Only text and image blocks are supported in message content!') }}
29
+ {%- endif %}
30
+ {%- endfor %}
31
+ {{- '[/INST]' }}
32
+ {%- endif %}
33
+ {%- elif message['role'] == 'system' %}
34
+ {%- if message['content'] is string %}
35
+ {{- '[SYSTEM_PROMPT]' + message['content'] + '[/SYSTEM_PROMPT]' }}
36
+ {%- else %}
37
+ {{- '[SYSTEM_PROMPT]' + message['content'][0]['text'] + '[/SYSTEM_PROMPT]' }}
38
+ {%- endif %}
39
+ {%- elif message['role'] == 'assistant' %}
40
+ {%- if message['content'] is string %}
41
+ {{- message['content'] + eos_token }}
42
+ {%- else %}
43
+ {{- message['content'][0]['text'] + eos_token }}
44
+ {%- endif %}
45
+ {%- else %}
46
+ {{- raise_exception('Only user, system and assistant roles are supported!') }}
47
+ {%- endif %}
48
+ {%- endfor %}
config.json CHANGED
@@ -15,12 +15,14 @@
15
  "num_attention_heads": 32,
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  "num_hidden_layers": 40,
17
  "num_key_value_heads": 8,
 
18
  "rms_norm_eps": 1e-05,
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  "rope_theta": 1000000000.0,
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  "sliding_window": null,
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  "tie_word_embeddings": false,
22
  "torch_dtype": "bfloat16",
23
- "transformers_version": "4.51.3",
 
24
  "use_cache": true,
25
  "vocab_size": 131072
26
  }
 
15
  "num_attention_heads": 32,
16
  "num_hidden_layers": 40,
17
  "num_key_value_heads": 8,
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+ "pad_token_id": 11,
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  "rms_norm_eps": 1e-05,
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  "rope_theta": 1000000000.0,
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  "sliding_window": null,
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  "tie_word_embeddings": false,
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  "torch_dtype": "bfloat16",
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+ "transformers_version": "4.52.2",
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+ "unsloth_fixed": true,
26
  "use_cache": true,
27
  "vocab_size": 131072
28
  }
generation_config.json CHANGED
@@ -2,5 +2,10 @@
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  "_from_model_config": true,
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  "bos_token_id": 1,
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  "eos_token_id": 2,
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- "transformers_version": "4.51.3"
 
 
 
 
 
6
  }
 
2
  "_from_model_config": true,
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  "bos_token_id": 1,
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  "eos_token_id": 2,
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+ "max_length": 131072,
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+ "pad_token_id": 11,
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+ "transformers_version": "4.52.2",
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+ "temperature": 0.15,
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+ "top_k": 40,
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+ "top_p": 0.95
11
  }
params.json CHANGED
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  "n_kv_heads": 8,
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  "rope_theta": 1000000000.0,
9
  "norm_eps": 1e-05,
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- "vocab_size": 131072,
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- "max_position_embeddings": 131072
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  }
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7
  "n_kv_heads": 8,
8
  "rope_theta": 1000000000.0,
9
  "norm_eps": 1e-05,
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+ "vocab_size": 131072
 
11
  }
12
 
special_tokens_map.json ADDED
@@ -0,0 +1,1032 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "additional_special_tokens": [
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+ "<unk>",
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+ "<s>",
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+ "</s>",
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+ "[INST]",
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+ "[/INST]",
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+ "[AVAILABLE_TOOLS]",
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+ "[/AVAILABLE_TOOLS]",
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+ "[TOOL_RESULTS]",
11
+ "[/TOOL_RESULTS]",
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+ "[TOOL_CALLS]",
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+ "[IMG]",
14
+ "<pad>",
15
+ "[IMG_BREAK]",
16
+ "[IMG_END]",
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+ "[PREFIX]",
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+ "[MIDDLE]",
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+ "[SUFFIX]",
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+ "[SYSTEM_PROMPT]",
21
+ "[/SYSTEM_PROMPT]",
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+ "[TOOL_CONTENT]",
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+ "<SPECIAL_20>",
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+ "<SPECIAL_21>",
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+ "<SPECIAL_22>",
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+ "<SPECIAL_23>",
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+ "<SPECIAL_24>",
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+ "<SPECIAL_25>",
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+ "<SPECIAL_26>",
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+ "<SPECIAL_27>",
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+ "<SPECIAL_28>",
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+ "<SPECIAL_29>",
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+ "<SPECIAL_30>",
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+ "<SPECIAL_31>",
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+ "<SPECIAL_32>",
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+ "<SPECIAL_33>",
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+ "<SPECIAL_34>",
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+ "<SPECIAL_35>",
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+ "<SPECIAL_36>",
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+ "<SPECIAL_37>",
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+ "<SPECIAL_38>",
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+ "<SPECIAL_39>",
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+ "<SPECIAL_40>",
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+ "<SPECIAL_41>",
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+ "<SPECIAL_42>",
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+ "<SPECIAL_43>",
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+ "<SPECIAL_44>",
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+ "<SPECIAL_45>",
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+ "<SPECIAL_46>",
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+ "<SPECIAL_47>",
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+ "<SPECIAL_48>",
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+ "<SPECIAL_49>",
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+ "<SPECIAL_50>",
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+ "<SPECIAL_51>",
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+ "<SPECIAL_52>",
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+ "<SPECIAL_53>",
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+ "<SPECIAL_54>",
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+ "<SPECIAL_55>",
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+ "<SPECIAL_56>",
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+ "<SPECIAL_57>",
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+ "<SPECIAL_58>",
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+ "<SPECIAL_59>",
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+ "<SPECIAL_60>",
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+ "<SPECIAL_61>",
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+ "<SPECIAL_62>",
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+ "<SPECIAL_63>",
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+ "<SPECIAL_64>",
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+ "<SPECIAL_65>",
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+ "<SPECIAL_66>",
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+ "<SPECIAL_67>",
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+ "<SPECIAL_68>",
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+ "<SPECIAL_69>",
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+ "<SPECIAL_70>",
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+ "<SPECIAL_71>",
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+ "<SPECIAL_72>",
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+ "<SPECIAL_73>",
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+ "<SPECIAL_74>",
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+ "<SPECIAL_75>",
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+ "<SPECIAL_76>",
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+ "<SPECIAL_77>",
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+ "<SPECIAL_78>",
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+ "<SPECIAL_79>",
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+ "<SPECIAL_80>",
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+ "<SPECIAL_81>",
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+ "<SPECIAL_82>",
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+ "<SPECIAL_83>",
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+ "<SPECIAL_84>",
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+ "<SPECIAL_85>",
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+ "<SPECIAL_86>",
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+ "<SPECIAL_87>",
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+ "<SPECIAL_88>",
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+ "<SPECIAL_89>",
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+ "<SPECIAL_90>",
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+ "<SPECIAL_91>",
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+ "<SPECIAL_92>",
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+ "<SPECIAL_103>",
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+ "<SPECIAL_104>",
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+ "<SPECIAL_106>",
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+ "<SPECIAL_108>",
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+ "<SPECIAL_109>",
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+ "<SPECIAL_110>",
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+ "<SPECIAL_111>",
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+ "<SPECIAL_164>",
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+ "<SPECIAL_167>",
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+ "<SPECIAL_171>",
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+ "<SPECIAL_172>",
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+ "<SPECIAL_174>",
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+ "<SPECIAL_175>",
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+ "<SPECIAL_212>",
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+ "<SPECIAL_216>",
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+ "<SPECIAL_218>",
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+ "<SPECIAL_219>",
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+ "<SPECIAL_225>",
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+ "<SPECIAL_232>",
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+ "<SPECIAL_235>",
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+ "<SPECIAL_236>",
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+ "<SPECIAL_237>",
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+ "<SPECIAL_239>",
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+ "<SPECIAL_243>",
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+ "<SPECIAL_245>",
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+ "<SPECIAL_246>",
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+ "<SPECIAL_247>",
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+ "<SPECIAL_248>",
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+ "<SPECIAL_249>",
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+ "<SPECIAL_250>",
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+ "<SPECIAL_251>",
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+ "<SPECIAL_252>",
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+ "<SPECIAL_253>",
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+ "<SPECIAL_254>",
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+ "<SPECIAL_255>",
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+ "<SPECIAL_256>",
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+ "<SPECIAL_257>",
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+ "<SPECIAL_258>",
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+ "<SPECIAL_259>",
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+ "<SPECIAL_260>",
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+ "<SPECIAL_261>",
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+ "<SPECIAL_262>",
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+ "<SPECIAL_263>",
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+ "<SPECIAL_264>",
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+ "<SPECIAL_265>",
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+ "<SPECIAL_267>",
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