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VHELM update #2592
VHELM update #2592
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src/helm/clients/vision_language/huggingface_vision2seq_client.py
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- name: huggingface/llava-v1.6-vicuna-7b-hf | ||
model_name: uw-madison/llava-v1.6-vicuna-7b-hf | ||
tokenizer_name: hf-internal-testing/llama-tokenizer |
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Use the respective tokenizers (vicuna etc)?
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I think vicuna uses the llama tokenizer if I'm not mistaken.
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return {"predictions": [{"text": raw_response.candidates[0].text}]} | ||
if not candidates: |
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We should make this condition tighter... I'll send you a follow-up pull request to fix it.
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_models_lock: Lock = Lock() | ||
_models: Dict[str, Optional[Vision2SeqModelProcessor]] = { | ||
"HuggingFaceM4/idefics2-8b": None, |
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Any reason we need to explicitly declare models here? Most clients do not validate which model names are supported (because the list can change frequently).
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It was for name validation. Do you think I can just remove this line then?
Changes: