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README.md
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---
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license: apache-2.0
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---
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### Huggingface RWKV Finch 14B Model
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> HF compatible model for Finch-14B.
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The following demonstrates the improvements from Eagle 7B to Finch 14B
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| | [Eagle 7B](https://huggingface.co/RWKV/
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| --- | --- | --- | --- |
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| [ARC](https://github.com/EleutherAI/lm-evaluation-harness/tree/main/lm_eval/tasks/arc) | 39.59% | 41.47% | 46.33% |
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| [HellaSwag](https://github.com/EleutherAI/lm-evaluation-harness/tree/main/lm_eval/tasks/hellaswag) | 53.09% | 55.96% | 57.69% |
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Assistant:"""
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model = AutoModelForCausalLM.from_pretrained("RWKV/
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tokenizer = AutoTokenizer.from_pretrained("RWKV/
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text = "请介绍北京的旅游景点"
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prompt = generate_prompt(text)
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Assistant:"""
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model = AutoModelForCausalLM.from_pretrained("RWKV/
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tokenizer = AutoTokenizer.from_pretrained("RWKV/
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text = "介绍一下大熊猫"
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prompt = generate_prompt(text)
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Assistant:"""
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model = AutoModelForCausalLM.from_pretrained("RWKV/
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tokenizer = AutoTokenizer.from_pretrained("RWKV/
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texts = ["请介绍北京的旅游景点", "介绍一下大熊猫", "乌兰察布"]
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prompts = [generate_prompt(text) for text in texts]
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## Acknowledgement
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We are grateful for the help and support from the following key groups:
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- [Recursal.ai](https://recursal.ai) team for financing the GPU resources, and managing the training of this foundation model - you can run the
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- EleutherAI for their support, especially in the v5/v6 Eagle/Finch paper
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- Linux Foundation AI & Data group for supporting and hosting the RWKV project
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### Huggingface RWKV Finch 14B Model
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> HF compatible model for Finch-14B.
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The following demonstrates the improvements from Eagle 7B to Finch 14B
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| | [Eagle 7B](https://huggingface.co/RWKV/v5-Eagle-7B-HF) | [Finch 7B](https://huggingface.co/RWKV/v6-Finch-7B-HF) | [Finch 14B](https://huggingface.co/RWKV/v6-Finch-14B-HF) |
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| --- | --- | --- | --- |
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| [ARC](https://github.com/EleutherAI/lm-evaluation-harness/tree/main/lm_eval/tasks/arc) | 39.59% | 41.47% | 46.33% |
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| [HellaSwag](https://github.com/EleutherAI/lm-evaluation-harness/tree/main/lm_eval/tasks/hellaswag) | 53.09% | 55.96% | 57.69% |
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Assistant:"""
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model = AutoModelForCausalLM.from_pretrained("RWKV/v5-Eagle-7B-HF", trust_remote_code=True).to(torch.float32)
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tokenizer = AutoTokenizer.from_pretrained("RWKV/v5-Eagle-7B-HF", trust_remote_code=True)
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text = "请介绍北京的旅游景点"
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prompt = generate_prompt(text)
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Assistant:"""
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model = AutoModelForCausalLM.from_pretrained("RWKV/v5-Eagle-7B-HF", trust_remote_code=True, torch_dtype=torch.float16).to(0)
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tokenizer = AutoTokenizer.from_pretrained("RWKV/v5-Eagle-7B-HF", trust_remote_code=True)
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text = "介绍一下大熊猫"
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prompt = generate_prompt(text)
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Assistant:"""
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model = AutoModelForCausalLM.from_pretrained("RWKV/v5-Eagle-7B-HF", trust_remote_code=True).to(torch.float32)
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tokenizer = AutoTokenizer.from_pretrained("RWKV/v5-Eagle-7B-HF", trust_remote_code=True)
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texts = ["请介绍北京的旅游景点", "介绍一下大熊猫", "乌兰察布"]
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prompts = [generate_prompt(text) for text in texts]
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## Acknowledgement
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We are grateful for the help and support from the following key groups:
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- [Recursal.ai](https://recursal.ai) team for financing the GPU resources, and managing the training of this foundation model - you can run the Eagle line of RWKV models on their cloud / on-premise platform today.
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- EleutherAI for their support, especially in the v5/v6 Eagle/Finch paper
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- Linux Foundation AI & Data group for supporting and hosting the RWKV project
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imgs/finch.jpg
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pytorch_model.bin
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