Instructions to use Blue7Bird/Claim_verification_Indic_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Blue7Bird/Claim_verification_Indic_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Blue7Bird/Claim_verification_Indic_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Blue7Bird/Claim_verification_Indic_bert") model = AutoModelForSequenceClassification.from_pretrained("Blue7Bird/Claim_verification_Indic_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from Blue7Bird/Claim_verification_Indic_bert: direct link, hf CLI and curl.
- Browser
- Download file 5.65 MB
-
https://huggingface.co/Blue7Bird/Claim_verification_Indic_bert/resolve/main/spiece.model
- Command line
-
hf download hf://Blue7Bird/Claim_verification_Indic_bert/spiece.model
-
curl -L -o spiece.model https://huggingface.co/Blue7Bird/Claim_verification_Indic_bert/resolve/main/spiece.model
5.65 MB
- Xet hash:
- cfaf15eddf5cbd3e8783281434fa1b5a12ca63fe62f1077f1e2d5a6729a79b04
- Size of remote file:
- 5.65 MB
- SHA256:
- 3a1173c2b6e144a02c001e289a05b5dbefddf247c50d4dcf42633158b2968fcb
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