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Qwen1.5-72B-Chat-4.65bpw-h6-exl2

Text Generation
Transformers
Safetensors
English
qwen2
chat
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
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  1. LICENSE +53 -0
  2. README.md +97 -0
  3. config.json +27 -0
  4. generation_config.json +13 -0
  5. merges.txt +0 -0
  6. model.safetensors.index.json +970 -0
  7. output-00001-of-00006.safetensors +3 -0
  8. output-00002-of-00006.safetensors +3 -0
  9. output-00003-of-00006.safetensors +3 -0
  10. output-00004-of-00006.safetensors +3 -0
  11. output-00005-of-00006.safetensors +3 -0
  12. output-00006-of-00006.safetensors +3 -0
  13. tokenizer.json +0 -0
  14. tokenizer_config.json +40 -0
  15. vocab.json +0 -0
LICENSE ADDED
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+ Tongyi Qianwen LICENSE AGREEMENT
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+
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+ Tongyi Qianwen Release Date: August 3, 2023
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+
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+ By clicking to agree or by using or distributing any portion or element of the Tongyi Qianwen Materials, you will be deemed to have recognized and accepted the content of this Agreement, which is effective immediately.
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+
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+ 1. Definitions
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+ a. This Tongyi Qianwen LICENSE AGREEMENT (this "Agreement") shall mean the terms and conditions for use, reproduction, distribution and modification of the Materials as defined by this Agreement.
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+ b. "We"(or "Us") shall mean Alibaba Cloud.
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+ c. "You" (or "Your") shall mean a natural person or legal entity exercising the rights granted by this Agreement and/or using the Materials for any purpose and in any field of use.
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+ d. "Third Parties" shall mean individuals or legal entities that are not under common control with Us or You.
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+ e. "Tongyi Qianwen" shall mean the large language models (including Qwen model and Qwen-Chat model), and software and algorithms, consisting of trained model weights, parameters (including optimizer states), machine-learning model code, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Us.
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+ f. "Materials" shall mean, collectively, Alibaba Cloud's proprietary Tongyi Qianwen and Documentation (and any portion thereof) made available under this Agreement.
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+ g. "Source" form shall mean the preferred form for making modifications, including but not limited to model source code, documentation source, and configuration files.
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+ h. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation,
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+ and conversions to other media types.
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+ 2. Grant of Rights
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+ 4. Restrictions
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+ If you are commercially using the Materials, and your product or service has more than 100 million monthly active users, You shall request a license from Us. You cannot exercise your rights under this Agreement without our express authorization.
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+
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+ 5. Rules of use
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+ a. The Materials may be subject to export controls or restrictions in China, the United States or other countries or regions. You shall comply with applicable laws and regulations in your use of the Materials.
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+ b. You can not use the Materials or any output therefrom to improve any other large language model (excluding Tongyi Qianwen or derivative works thereof).
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+
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+ 6. Intellectual Property
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+ a. We retain ownership of all intellectual property rights in and to the Materials and derivatives made by or for Us. Conditioned upon compliance with the terms and conditions of this Agreement, with respect to any derivative works and modifications of the Materials that are made by you, you are and will be the owner of such derivative works and modifications.
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+ 7. Disclaimer of Warranty and Limitation of Liability
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+ a. We are not obligated to support, update, provide training for, or develop any further version of the Tongyi Qianwen Materials or to grant any license thereto.
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+ b. THE MATERIALS ARE PROVIDED "AS IS" WITHOUT ANY EXPRESS OR IMPLIED WARRANTY OF ANY KIND INCLUDING WARRANTIES OF MERCHANTABILITY, NONINFRINGEMENT, OR FITNESS FOR A PARTICULAR PURPOSE. WE MAKE NO WARRANTY AND ASSUME NO RESPONSIBILITY FOR THE SAFETY OR STABILITY OF THE MATERIALS AND ANY OUTPUT THEREFROM.
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+ a. The term of this Agreement shall commence upon your acceptance of this Agreement or access to the Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein.
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+ b. We may terminate this Agreement if you breach any of the terms or conditions of this Agreement. Upon termination of this Agreement, you must delete and cease use of the Materials. Sections 7 and 9 shall survive the termination of this Agreement.
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+ 9. Governing Law and Jurisdiction.
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+ a. This Agreement and any dispute arising out of or relating to it will be governed by the laws of China, without regard to conflict of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement.
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+ b. The People's Courts in Hangzhou City shall have exclusive jurisdiction over any dispute arising out of this Agreement.
README.md ADDED
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1
+ ---
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+ license: other
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+ license_name: tongyi-qianwen
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+ license_link: >-
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+ https://huggingface.co/Qwen/Qwen1.5-72B-Chat/blob/main/LICENSE
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ tags:
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+ - chat
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+ ---
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+
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+ # Qwen1.5-72B-Chat
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+
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+
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+ ## Introduction
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+
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+ Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. In comparison with the previous released Qwen, the improvements include:
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+
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+ * 6 model sizes, including 0.5B, 1.8B, 4B, 7B, 14B, and 72B;
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+ * Significant performance improvement in human preference for chat models;
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+ * Multilingual support of both base and chat models;
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+ * Stable support of 32K context length for models of all sizes
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+ * No need of `trust_remote_code`.
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+
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+ For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen1.5/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5).
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+ <br>
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+
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+ ## Model Details
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+ Qwen1.5 is a language model series including decoder language models of different model sizes. For each size, we release the base language model and the aligned chat model. It is based on the Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, mixture of sliding window attention and full attention, etc. Additionally, we have an improved tokenizer adaptive to multiple natural languages and codes. For the beta version, temporarily we did not include GQA and the mixture of SWA and full attention.
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+
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+ ## Training details
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+ We pretrained the models with a large amount of data, and we post-trained the models with both supervised finetuning and direct preference optimization. However, DPO leads to improvements in human preference evaluation but degradation in benchmark evaluation. In the very near future, we will fix both problems.
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+
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+ ## Requirements
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+ The code of Qwen1.5 has been in the latest Hugging face transformers and we advise you to install `transformers>=4.37.0`, or you might encounter the following error:
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+ ```
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+ KeyError: 'qwen2'
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+ ```
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+
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+ ## Quickstart
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+
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+ Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ device = "cuda" # the device to load the model onto
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "Qwen/Qwen1.5-72B-Chat",
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+ device_map="auto"
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-72B-Chat")
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+
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+ prompt = "Give me a short introduction to large language model."
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+ messages = [
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+ {"role": "system", "content": "You are a helpful assistant."},
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+ {"role": "user", "content": prompt}
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+ ]
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+ text = tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
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+ )
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+ model_inputs = tokenizer([text], return_tensors="pt").to(device)
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+
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+ generated_ids = model.generate(
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+ model_inputs.input_ids,
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+ max_new_tokens=512
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+ )
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+ generated_ids = [
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+ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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+ ]
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+
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+ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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+ ```
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+
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+ For quantized models, we advise you to use the GPTQ, AWQ, and GGUF correspondents, namely `Qwen1.5-72B-Chat-GPTQ-Int4`, `Qwen1.5-72B-Chat-GPTQ-Int8`, `Qwen1.5-72B-Chat-AWQ`, and `Qwen1.5-72B-Chat-GGUF`.
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+
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+
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+ ## Tips
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+
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+ * If you encounter code switching or other bad cases, we advise you to use our provided hyper-parameters in `generation_config.json`.
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+
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+
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+ ## Citation
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+
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+ If you find our work helpful, feel free to give us a cite.
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+
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+ ```
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+ @article{qwen,
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+ title={Qwen Technical Report},
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+ author={Jinze Bai and Shuai Bai and Yunfei Chu and Zeyu Cui and Kai Dang and Xiaodong Deng and Yang Fan and Wenbin Ge and Yu Han and Fei Huang and Binyuan Hui and Luo Ji and Mei Li and Junyang Lin and Runji Lin and Dayiheng Liu and Gao Liu and Chengqiang Lu and Keming Lu and Jianxin Ma and Rui Men and Xingzhang Ren and Xuancheng Ren and Chuanqi Tan and Sinan Tan and Jianhong Tu and Peng Wang and Shijie Wang and Wei Wang and Shengguang Wu and Benfeng Xu and Jin Xu and An Yang and Hao Yang and Jian Yang and Shusheng Yang and Yang Yao and Bowen Yu and Hongyi Yuan and Zheng Yuan and Jianwei Zhang and Xingxuan Zhang and Yichang Zhang and Zhenru Zhang and Chang Zhou and Jingren Zhou and Xiaohuan Zhou and Tianhang Zhu},
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+ journal={arXiv preprint arXiv:2309.16609},
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+ year={2023}
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+ }
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+ ```
config.json ADDED
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+ {
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+ "architectures": [
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+ "Qwen2ForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 151643,
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+ "eos_token_id": 151643,
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+ "hidden_act": "silu",
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+ "hidden_size": 8192,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 24576,
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+ "max_position_embeddings": 32768,
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+ "max_window_layers": 70,
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+ "model_type": "qwen2",
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+ "num_attention_heads": 64,
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+ "num_hidden_layers": 80,
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+ "num_key_value_heads": 64,
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+ "rms_norm_eps": 1e-06,
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+ "rope_theta": 1000000.0,
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+ "sliding_window": 32768,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.37.0",
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+ "use_cache": true,
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+ "use_sliding_window": false,
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+ "vocab_size": 152064
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+ }
generation_config.json ADDED
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+ {
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+ "bos_token_id": 151643,
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+ "do_sample": true,
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+ "eos_token_id": [
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+ 151645,
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+ 151643
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+ ],
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+ "repetition_penalty": 1.05,
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+ "temperature": 0.7,
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+ "top_p": 0.8,
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+ "top_k": 20,
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+ "transformers_version": "4.37.0"
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+ }
merges.txt ADDED
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