Instructions to use Harini2506/scibert_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harini2506/scibert_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Harini2506/scibert_1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Harini2506/scibert_1") model = AutoModelForTokenClassification.from_pretrained("Harini2506/scibert_1") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f9f5650e90690fe297af8fec40cd41b039e4a7dda3833638dfce89410a64353c
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size 554477012
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