Instructions to use predibase/bc5cdr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use predibase/bc5cdr with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "predibase/bc5cdr") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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pipeline_tag: text-generation
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Description: 1500 PubMed articles with 4409 annotated chemicals, 5818 diseases and 3116 chemical-disease interactions.\
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Original dataset: bc5cdr \
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Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
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The adapter_category is Named Entity Recognition and the name is Chemical and Disease Recognition (bc5cdr)\
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pipeline_tag: text-generation
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Description: 1500 PubMed articles with 4409 annotated chemicals, 5818 diseases and 3116 chemical-disease interactions.\
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Original dataset: https://huggingface.co/datasets/tner/bc5cdr \
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Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
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The adapter_category is Named Entity Recognition and the name is Chemical and Disease Recognition (bc5cdr)\
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