Instructions to use jjzha/escoxlmr_knowledge_extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jjzha/escoxlmr_knowledge_extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jjzha/escoxlmr_knowledge_extraction")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jjzha/escoxlmr_knowledge_extraction") model = AutoModelForTokenClassification.from_pretrained("jjzha/escoxlmr_knowledge_extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (7f4487bcdf9912b42e1b2c925a681bfe8409ea47) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>11ff791
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Create config.json
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Delete config.json
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add knowledge extraction model
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add json to lfs
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initial commit
Mike Zhang2768f56