Instructions to use l3cube-pune/marathi-sentiment-md with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-sentiment-md with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/marathi-sentiment-md")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-sentiment-md") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/marathi-sentiment-md") - Notebooks
- Google Colab
- Kaggle
Commit ·
0c3d6b4
1
Parent(s): 0607605
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (47699f9783b3027c70c3fda6b6dfaf9b2b400025)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b6ad9c793eb3a37f9a8a1c53d82822f667c2724a32acdf7096853c18148ba882
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size 950261860
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