Instructions to use vitthalbhandari/incremental-semi-supervised-training-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vitthalbhandari/incremental-semi-supervised-training-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vitthalbhandari/incremental-semi-supervised-training-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vitthalbhandari/incremental-semi-supervised-training-base") model = AutoModelForSequenceClassification.from_pretrained("vitthalbhandari/incremental-semi-supervised-training-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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 sha256:11fb252bf5a094c9b42f13f42dabb5cdd5b3ca2e8f5cf657d0948ca51cc59e0d
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size 1421499616
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