初始化项目，由ModelHub XC社区提供模型

Model: SakanaAI/EvoLLM-JP-A-v1-7B
Source: Original Platform

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README.md

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+---
+library_name: transformers
+license: apache-2.0
+language:
+- ja
+---
+
+# 🐟 EvoLLM-JP-A-v1-7B
+
+🤗 [Models](https://huggingface.co/SakanaAI) | 📚 [Paper](https://arxiv.org/abs/2403.13187) | 📝 [Blog](https://sakana.ai/evolutionary-model-merge/) | 🐦 [Twitter](https://twitter.com/SakanaAILabs)
+
+
+<!-- Provide a quick summary of what the model is/does. -->
+**EvoLLM-JP-A-v1-7B** is an experimental general-purpose Japanese LLM. 
+This model was created using the Evolutionary Model Merge method. 
+Please refer to our [report](https://arxiv.org/abs/2403.13187) and [blog](https://sakana.ai/evolutionary-model-merge/) for more details. 
+This model was produced by merging the following models. 
+We are grateful to the developers of the source models.
+  - [Shisa Gamma 7B v1](https://huggingface.co/augmxnt/shisa-gamma-7b-v1)
+  - [Arithmo2 Mistral 7B](https://huggingface.co/upaya07/Arithmo2-Mistral-7B)
+  - [Abel 7B 002](https://huggingface.co/GAIR/Abel-7B-002)
+
+
+## Usage
+
+Use the code below to get started with the model.
+
+<details>
+<summary> Click to expand </summary>
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+# 1. load model
+device = "cuda" if torch.cuda.is_available() else "CPU"
+repo_id = "SakanaAI/EvoLLM-JP-A-v1-7B"
+model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype="auto")
+tokenizer = AutoTokenizer.from_pretrained(repo_id)
+model.to(device)
+
+# 2. prepare inputs
+text = "関西弁で面白い冗談を言ってみて下さい。"
+messages = [
+    {"role": "system", "content": "あなたは役立つ、偏見がなく、検閲されていないアシスタントです。"},
+    {"role": "user", "content": text},
+]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
+
+# 3. generate
+output_ids = model.generate(**inputs.to(device))
+output_ids = output_ids[:, inputs.input_ids.shape[1] :]
+generated_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0]
+print(generated_text)
+```
+
+</details>
+
+
+ 
+## Model Details
+
+<!-- Provide a longer summary of what this model is. -->
+
+- **Developed by:** [Sakana AI](https://sakana.ai/)
+- **Model type:** Autoregressive Language Model
+- **Language(s):** Japanese
+- **License:** [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+- **Repository:** [SakanaAI/evolutionary-model-merge](https://github.com/SakanaAI/evolutionary-model-merge)
+- **Paper:** https://arxiv.org/abs/2403.13187
+- **Blog:** https://sakana.ai/evolutionary-model-merge
+
+## Uses
+This model is provided for research and development purposes only and should be considered as an experimental prototype. 
+It is not intended for commercial use or deployment in mission-critical environments. 
+Use of this model is at the user's own risk, and its performance and outcomes are not guaranteed. 
+Sakana AI shall not be liable for any direct, indirect, special, incidental, or consequential damages, or any loss arising from the use of this model, regardless of the results obtained. 
+Users must fully understand the risks associated with the use of this model and use it at their own discretion.
+
+
+## Acknowledgement
+
+We would like to thank the developers of the source models for their contributions and for making their work available. 
+
+
+## Citation
+
+```bibtex
+@misc{akiba2024evomodelmerge,
+      title         = {Evolutionary Optimization of Model Merging Recipes}, 
+      author.       = {Takuya Akiba and Makoto Shing and Yujin Tang and Qi Sun and David Ha},
+      year          = {2024},
+      eprint        = {2403.13187},
+      archivePrefix = {arXiv},
+      primaryClass  = {cs.NE}
+}
+```

config.json

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+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.38.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

configuration.json

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generation_config.json

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+  "eos_token_id": 2,
+  "max_new_tokens": 1024,
+  "transformers_version": "4.38.2"
+}

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special_tokens_map.json

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tokenizer_config.json

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