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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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  ![Finch Bird](./imgs/finch.jpg)
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  > **! Important Note !**
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  >
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- > The following is the HF transformers implementation of the Finch 14B model. This is meant to be used with the huggingface transformers
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  >
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  >
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@@ -18,15 +18,15 @@ license: apache-2.0
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  ## Quickstart with the hugging face transformer library
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  ```
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- model = AutoModelForCausalLM.from_pretrained("RWKV/v6-Finch-14B-HF", trust_remote_code=True).to(torch.float32)
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- tokenizer = AutoTokenizer.from_pretrained("RWKV/v6-Finch-14B-HF", trust_remote_code=True)
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  ```
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  ## Evaluation
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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% |
@@ -59,8 +59,8 @@ User: {instruction}
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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)
@@ -115,8 +115,8 @@ User: {instruction}
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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)
@@ -162,8 +162,8 @@ User: {instruction}
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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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  ---
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  license: apache-2.0
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  ---
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+ ### Huggingface RWKV Finch 7B Model
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+ > HF compatible model for Finch-7B.
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  ![Finch Bird](./imgs/finch.jpg)
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  > **! Important Note !**
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  >
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+ > The following is the HF transformers implementation of the Finch 7B model. This is meant to be used with the huggingface transformers
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  >
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  >
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  ## Quickstart with the hugging face transformer library
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  ```
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+ model = AutoModelForCausalLM.from_pretrained("RWKV/v6-Finch-7B-HF", trust_remote_code=True).to(torch.float32)
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+ tokenizer = AutoTokenizer.from_pretrained("RWKV/v6-Finch-7B-HF", trust_remote_code=True)
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  ```
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  ## Evaluation
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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/v6-Finch-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/v6-Finch-7B-HF", trust_remote_code=True).to(torch.float32)
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+ tokenizer = AutoTokenizer.from_pretrained("RWKV/v6-Finch-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/v6-Finch-7B-HF", trust_remote_code=True, torch_dtype=torch.float16).to(0)
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+ tokenizer = AutoTokenizer.from_pretrained("RWKV/v6-Finch-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/v6-Finch-7B-HF", trust_remote_code=True).to(torch.float32)
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+ tokenizer = AutoTokenizer.from_pretrained("RWKV/v6-Finch-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]