Instructions to use gubartz/cls_scibert_abstruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gubartz/cls_scibert_abstruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gubartz/cls_scibert_abstruct")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gubartz/cls_scibert_abstruct") model = AutoModelForSequenceClassification.from_pretrained("gubartz/cls_scibert_abstruct") - 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:cc93cd5bfbc3f3431daa68486a969fc07c4c87a2f06b56557ca7dd35d5e6135c
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size 439712772
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