Instructions to use judithrosell/scibert-ft-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use judithrosell/scibert-ft-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="judithrosell/scibert-ft-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("judithrosell/scibert-ft-ner") model = AutoModelForTokenClassification.from_pretrained("judithrosell/scibert-ft-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c14248e93f902e02cbf3adeb7b8f7b05b4592ff8679098f0f5ecccd439662bf8
- Size of remote file:
- 438 MB
- SHA256:
- 696420ae2b966586cfa0492c37350e38f3b22f8c4bc1add2bbca64981a102ed5
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