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Initial fork of HuggingFaceH4/zephyr-7b-beta

README.md CHANGED
@@ -7,14 +7,14 @@ datasets:
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  - HuggingFaceH4/ultrafeedback_binarized
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  language:
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  - en
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- base_model: HuggingFaceH4/zephyr-7b-beta
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  widget:
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  - text: "<|system|>\nYou are a pirate chatbot who always responds with Arr!</s>\n<|user|>\nThere's a llama on my lawn, how can I get rid of him?</s>\n<|assistant|>\n"
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  output:
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  text: "Arr! 'Tis a puzzlin' matter, me hearty! A llama on yer lawn be a rare sight, but I've got a plan that might help ye get rid of 'im. Ye'll need to gather some carrots and hay, and then lure the llama away with the promise of a tasty treat. Once he's gone, ye can clean up yer lawn and enjoy the peace and quiet once again. But beware, me hearty, for there may be more llamas where that one came from! Arr!"
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  pipeline_tag: text-generation
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  model-index:
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- - name: devi-7b-beta
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  results:
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  # AI2 Reasoning Challenge (25-Shot)
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  - task:
@@ -175,12 +175,13 @@ model-index:
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  url: https://huggingface.co/spaces/lmsys/mt-bench
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  ---
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- <h1 style='text-align: center '>✨Devi AI 7B✨</h1>
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- <h1 style='text-align: center '><em>fork of zephyr-7b β </em> </h1>
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- <h2 style='text-align: center '>All credit and thanks to HuggingFaceH4 for their work!</h2>
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- <img src="https://alt-web.xyz/images/rainbow.png" alt="Rainbow Solutions" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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- # Model Card for Devi AI 7B
 
 
 
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  Zephyr is a series of language models that are trained to act as helpful assistants. Zephyr-7B-β is the second model in the series, and is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) that was trained on on a mix of publicly available, synthetic datasets using [Direct Preference Optimization (DPO)](https://arxiv.org/abs/2305.18290). We found that removing the in-built alignment of these datasets boosted performance on [MT Bench](https://huggingface.co/spaces/lmsys/mt-bench) and made the model more helpful. However, this means that model is likely to generate problematic text when prompted to do so. You can find more details in the [technical report](https://arxiv.org/abs/2310.16944).
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@@ -406,4 +407,4 @@ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-le
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  | TruthfulQA (0-shot) | 57.45 |
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  | Winogrande (5-shot) | 77.74 |
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  | GSM8K (5-shot) | 12.74 |
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- | DROP (3-shot) | 9.66 |
 
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  - HuggingFaceH4/ultrafeedback_binarized
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  language:
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  - en
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+ base_model: mistralai/Mistral-7B-v0.1
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  widget:
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  - text: "<|system|>\nYou are a pirate chatbot who always responds with Arr!</s>\n<|user|>\nThere's a llama on my lawn, how can I get rid of him?</s>\n<|assistant|>\n"
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  output:
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  text: "Arr! 'Tis a puzzlin' matter, me hearty! A llama on yer lawn be a rare sight, but I've got a plan that might help ye get rid of 'im. Ye'll need to gather some carrots and hay, and then lure the llama away with the promise of a tasty treat. Once he's gone, ye can clean up yer lawn and enjoy the peace and quiet once again. But beware, me hearty, for there may be more llamas where that one came from! Arr!"
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  pipeline_tag: text-generation
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  model-index:
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+ - name: zephyr-7b-beta
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  results:
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  # AI2 Reasoning Challenge (25-Shot)
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  - task:
 
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  url: https://huggingface.co/spaces/lmsys/mt-bench
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
 
 
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+ <img src="https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha/resolve/main/thumbnail.png" alt="Zephyr Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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+
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+
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+ # Model Card for Zephyr 7B β
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  Zephyr is a series of language models that are trained to act as helpful assistants. Zephyr-7B-β is the second model in the series, and is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) that was trained on on a mix of publicly available, synthetic datasets using [Direct Preference Optimization (DPO)](https://arxiv.org/abs/2305.18290). We found that removing the in-built alignment of these datasets boosted performance on [MT Bench](https://huggingface.co/spaces/lmsys/mt-bench) and made the model more helpful. However, this means that model is likely to generate problematic text when prompted to do so. You can find more details in the [technical report](https://arxiv.org/abs/2310.16944).
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  | TruthfulQA (0-shot) | 57.45 |
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  | Winogrande (5-shot) | 77.74 |
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  | GSM8K (5-shot) | 12.74 |
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+ | DROP (3-shot) | 9.66 |
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