Instructions to use l3cube-pune/marathi-paraphrase-detection-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-paraphrase-detection-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/marathi-paraphrase-detection-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-paraphrase-detection-bert") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/marathi-paraphrase-detection-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from l3cube-pune/marathi-paraphrase-detection-bert: direct link, hf CLI and curl.
- Browser
- Download file 950 MB
-
https://huggingface.co/l3cube-pune/marathi-paraphrase-detection-bert/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://l3cube-pune/marathi-paraphrase-detection-bert@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/l3cube-pune/marathi-paraphrase-detection-bert/resolve/refs%2Fpr%2F1/model.safetensors
950 MB
- Xet hash:
- de843276067621189d43851717ba585151dff043c6a3bedd6c700b78e0f1723f
- Size of remote file:
- 950 MB
- SHA256:
- 168ae3cd2f37325c9fb176efd23a827417cfe84588258a63762ea96399fad454
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