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README.md
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## Original Model
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This model is finetuned on WebLINX using checkpoints previously published on Huggingface Hub.\
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</div>
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## Quickstart
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```python
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from datasets import load_dataset
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from huggingface_hub import snapshot_download
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from transformers import pipeline
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# Load validation split
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valid = load_dataset("McGill-NLP/weblinx", split="validation")
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# Download and load the templates
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snapshot_download(
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"McGill-NLP/WebLINX", repo_type="dataset", allow_patterns="templates/*.txt", local_dir="./"
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)
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with open('templates/llama.txt') as f:
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template = f.read()
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turn = valid[0]
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turn_text = template.format(**turn)
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# Load action model and input the text to get prediction
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action_model = pipeline(
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model="McGill-NLP/Llama-2-7b-chat-weblinx", device=0, torch_dtype='auto'
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)
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out = action_model(turn_text, return_full_text=False, max_new_tokens=64, truncation=True)
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pred = out[0]['generated_text']
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print("Ref:", turn["action"])
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print("Pred:", pred)
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```
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## Original Model
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This model is finetuned on WebLINX using checkpoints previously published on Huggingface Hub.\
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