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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2-1.5B
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen2
+datasets:
+- Replete-AI/code_bagel_hermes-2.5
+- Replete-AI/code_bagel
+- Replete-AI/OpenHermes-2.5-Uncensored
+- teknium/OpenHermes-2.5
+- layoric/tiny-codes-alpaca
+- glaiveai/glaive-code-assistant-v3
+- ajibawa-2023/Code-290k-ShareGPT
+- TIGER-Lab/MathInstruct
+- chargoddard/commitpack-ft-instruct-rated
+- iamturun/code_instructions_120k_alpaca
+- ise-uiuc/Magicoder-Evol-Instruct-110K
+- cognitivecomputations/dolphin-coder
+- nickrosh/Evol-Instruct-Code-80k-v1
+- coseal/CodeUltraFeedback_binarized
+- glaiveai/glaive-function-calling-v2
+- CyberNative/Code_Vulnerability_Security_DPO
+- jondurbin/airoboros-2.2
+- camel-ai
+- lmsys/lmsys-chat-1m
+- CollectiveCognition/chats-data-2023-09-22
+- CoT-Alpaca-GPT4
+- WizardLM/WizardLM_evol_instruct_70k
+- WizardLM/WizardLM_evol_instruct_V2_196k
+- teknium/GPT4-LLM-Cleaned
+- GPTeacher
+- OpenGPT
+- meta-math/MetaMathQA
+- Open-Orca/SlimOrca
+- garage-bAInd/Open-Platypus
+- anon8231489123/ShareGPT_Vicuna_unfiltered
+- Unnatural-Instructions-GPT4
+model-index:
+- name: Replete-Coder-llama3-8b
+  results:
+  - task:
+      name: HumanEval
+      type: text-generation
+    dataset:
+      type: openai_humaneval
+      name: HumanEval
+    metrics:
+    - name: pass@1
+      type: pass@1
+      value: 0.35365853658536583
+      verified: false
+  - task:
+      name: AI2 Reasoning Challenge
+      type: text-generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: accuracy
+      value: 
+      name: normalized accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: accuracy
+      value: 
+      name: normalized accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: accuracy
+      value: 
+      name: accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: multiple_choice_accuracy
+      value: 
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: accuracy
+      value: 
+      name: accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: accuracy
+      value: 
+      name: accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+
+---
+# Replete-Coder-Qwen2-1.5b
+Finetuned by: Rombodawg
+### More than just a coding model!
+Although Replete-Coder has amazing coding capabilities, its trained on vaste amount of non-coding data, fully cleaned and uncensored. Dont just use it for coding, use it for all your needs! We are truly trying to make the GPT killer!
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/-0dERC793D9XeFsJ9uHbx.png)
+
+Thank you to TensorDock for sponsoring Replete-Coder-llama3-8b and Replete-Coder-Qwen2-1.5b
+you can check out their website for cloud compute rental bellow. 
+- https://tensordock.com
+__________________________________________________________________________________________________
+Replete-Coder-Qwen2-1.5b is a general purpose model that is specially trained in coding in over 100 coding languages. The data used to train the model contains 25% non-code instruction data and 75% coding instruction data totaling up to 3.9 million lines, roughly 1 billion tokens, or 7.27gb of instruct data. The data used to train this model was 100% uncensored, then fully deduplicated, before training happened.
+
+The Replete-Coder models (including Replete-Coder-llama3-8b and Replete-Coder-Qwen2-1.5b) feature the following:
+
+- Advanced coding capabilities in over 100 coding languages
+- Advanced code translation (between languages)
+- Security and vulnerability prevention related coding capabilities
+- General purpose use
+- Uncensored use
+- Function calling
+- Advanced math use
+- Use on low end (8b) and mobile (1.5b) platforms
+
+Notice: Replete-Coder series of models are fine-tuned on a context window of 8192 tokens. Performance past this context window is not guaranteed.
+__________________________________________________________________________________________________
+
+You can find the 25% non-coding instruction below:
+
+-  https://huggingface.co/datasets/Replete-AI/OpenHermes-2.5-Uncensored
+
+And the 75% coding specific instruction data below:
+
+- https://huggingface.co/datasets/Replete-AI/code_bagel
+
+These two datasets were combined to create the final dataset for training, which is linked below:
+
+- https://huggingface.co/datasets/Replete-AI/code_bagel_hermes-2.5
+__________________________________________________________________________________________________
+## Prompt Template: ChatML
+```
+<|im_start|>system
+{}<|im_end|>
+
+<|im_start|>user
+{}<|im_end|>
+
+<|im_start|>assistant
+{}
+```
+Note: The system prompt varies in training data, but the most commonly used one is:
+```
+Below is an instruction that describes a task, Write a response that appropriately completes the request.
+```
+End token:
+```
+<|endoftext|>
+```
+__________________________________________________________________________________________________
+Thank you to the community for your contributions to the Replete-AI/code_bagel_hermes-2.5 dataset. Without the participation of so many members making their datasets free and open source for any to use, this amazing AI model wouldn't be possible.
+
+Extra special thanks to Teknium for the Open-Hermes-2.5 dataset and jondurbin for the bagel dataset and the naming idea for the code_bagel series of datasets. You can find both of their huggingface accounts linked below:
+
+- https://huggingface.co/teknium
+- https://huggingface.co/jondurbin
+
+Another special thanks to unsloth for being the main method of training for Replete-Coder. Bellow you can find their github, as well as the special Replete-Ai secret sause (Unsloth + Qlora + Galore) colab code document that was used to train this model.
+
+- https://github.com/unslothai/unsloth
+- https://colab.research.google.com/drive/1eXGqy5M--0yW4u0uRnmNgBka-tDk2Li0?usp=sharing
+__________________________________________________________________________________________________
+
+## Join the Replete-Ai discord! We are a great and Loving community!
+
+- https://discord.gg/ZZbnsmVnjD

added_tokens.json

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+{
+  "<|PAD_TOKEN|>": 151646,
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644
+}

config.json

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+{
+    "_name_or_path": "rombodawg/Qwen2-1.5b-Reuploaded",
+    "architectures": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "eos_token_id": 151643,
+    "hidden_act": "silu",
+    "hidden_size": 1536,
+    "initializer_range": 0.02,
+    "intermediate_size": 8960,
+    "max_position_embeddings": 131072,
+    "max_window_layers": 28,
+    "model_type": "qwen2",
+    "num_attention_heads": 12,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 2,
+    "pad_token_id": 151646,
+    "rms_norm_eps": 1e-06,
+    "rope_theta": 1000000.0,
+    "sliding_window": 131072,
+    "tie_word_embeddings": true,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.41.2",
+    "unsloth_version": "2024.6",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 151936,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.1.6",
+        "bits": 4.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 115,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.41.2"
+}

output.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9e54f06378e04c94b56183b8475b5cecdc8122f6979eb95461582fb6d76c9811
+size 1307640166

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|PAD_TOKEN|>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|PAD_TOKEN|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}