初始化项目，由ModelHub XC社区提供模型

Model: umd-zhou-lab/recycled-wizardlm-7b-v2.0
Source: Original Platform

.gitattributes

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README.md

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+---
+license: llama2
+language:
+- en
+---
+# Model Card for umd-zhou-lab/recycled-wizardlm-7b-v2.0
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This model is trained by fine-tuning llama-2 with recycled WizardLM(70k) data V2.
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+- **Developed by:** UMD Tianyi Zhou Lab
+- **Model type:** An auto-regressive language model based on the transformer architecture
+- **License:** Llama 2 Community License Agreement
+- **Finetuned from model:** [meta-llama/Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b)
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
+
+- **GitHub:** [Reflection-Tuning](https://github.com/tianyi-lab/Reflection_Tuning)
+- **Paper:** [Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning](https://arxiv.org/abs/2310.11716)
+- **Data:** Coming soon
+
+## Uses
+
+The primary use of this model is research on large language models and chatbots. 
+The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
+
+## Training
+
+We use the prompt from [FastChat](https://github.com/lm-sys/FastChat):
+
+```
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: Hi ASSISTANT: Hello.</s>USER: Who are you? ASSISTANT: I am ...</s>......
+```
+
+| Hyperparameter | Global Batch Size | Learning rate | Epochs | Max length | Weight decay | Warmup Rate |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: |
+| Recycled Models (7B) | 128 | 2e-5 | 3 | 2048 | 0 | 0.03 |
+
+## Performance
+
+The following table provides a comparison between our recycled models (V2) and baseline models on the AlpacaEval Leaderboard and Huggingface Open LLM Leaderboard. <br>
+
+The V2 Recycled Alpaca Data and WizardLM data, and the corresponding paper will be released soon. 
+
+|                          | **AlpacaEval** || **Avg** | **ARC** | **HellaSwag** | **MMLU** | **TruthfulQA** || **Model**|
+|--------------------------|:--------------:|:-:|:-----------:|:-------:|:-------------:|:-------:|:--------------:|:-:|:-:|
+| **Alpaca 7B**            | 26.46          || 50.21       | 42.65   | 76.91         | 41.73   | 39.55          ||/|
+| **Recycled Alpaca 7B V2.0**   |     79.58      || 56.05 |  54.01  |   78.07      |  46.69  |    45.41       ||[[hf-Link]](https://huggingface.co/umd-zhou-lab/recycled-alpaca-7b-v2.0)|
+|||||||||||
+| **WizardLM 7B**          | 67.64          || 54.18       | 51.60   | 77.70         | 42.70   | 44.70          ||/|
+| **Recycled WizardLM 7B V2.0** |     83.48      ||   56.79     |  54.78 |     77.86     |  45.63  |    48.91     ||[[hf-Link]](https://huggingface.co/umd-zhou-lab/recycled-wizardlm-7b-v2.0)|
+|||||||||
+
+
+## Citation
+
+Please consider citing our paper if you think our codes, data, or models are useful. Thank you!
+```
+@misc{li2023reflectiontuning,
+      title={Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning}, 
+      author={Ming Li and Lichang Chen and Jiuhai Chen and Shwai He and Heng Huang and Jiuxiang Gu and Tianyi Zhou},
+      year={2023},
+      eprint={2310.11716},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```

config.json

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+{
+  "_name_or_path": "meta-llama/Llama-2-7b-hf",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+  "pad_token_id": 0,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.32.1"
+}

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special_tokens_map.json

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+}

tokenizer_config.json

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