Instructions to use muratti18462/chem_ner_scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muratti18462/chem_ner_scratch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="muratti18462/chem_ner_scratch")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("muratti18462/chem_ner_scratch") model = AutoModelForTokenClassification.from_pretrained("muratti18462/chem_ner_scratch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa939808164e026ec017796145c8d3b16da8e0f32d74f36703d92d3d0bc87011
- Size of remote file:
- 5.24 kB
- SHA256:
- e53a7814bc81b4a53fa2d1ab3d5d9e0e93cf2f1982b099a05cd702b087cfd9f6
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