Instructions to use vitthalbhandari/incremental-semi-supervised-training-1mln-equal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vitthalbhandari/incremental-semi-supervised-training-1mln-equal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vitthalbhandari/incremental-semi-supervised-training-1mln-equal")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vitthalbhandari/incremental-semi-supervised-training-1mln-equal") model = AutoModelForSequenceClassification.from_pretrained("vitthalbhandari/incremental-semi-supervised-training-1mln-equal", device_map="auto") - 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 sha256:118550ff7eed0ed88e586da892978a9b48693480175c797beed51489b3441d5a
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size 1421499616
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