Instructions to use Oums/SSI_SciBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Oums/SSI_SciBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Oums/SSI_SciBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Oums/SSI_SciBERT") model = AutoModelForSequenceClassification.from_pretrained("Oums/SSI_SciBERT") - 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 sha256:815c1dd4dccbe140296eb782411dddd93430b9e50e45bbf0eca85f24758cbe5a
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size 439707728
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