Instructions to use gmguarino/climateguard_claim_extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gmguarino/climateguard_claim_extraction with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gmguarino/climateguard_claim_extraction") model = AutoModelForSeq2SeqLM.from_pretrained("gmguarino/climateguard_claim_extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from gmguarino/climateguard_claim_extraction: direct link, hf CLI and curl.
- Browser
- Download file 4.31 MB
-
https://huggingface.co/gmguarino/climateguard_claim_extraction/resolve/main/spiece.model
- Command line
-
hf download hf://gmguarino/climateguard_claim_extraction/spiece.model
-
curl -L -o spiece.model https://huggingface.co/gmguarino/climateguard_claim_extraction/resolve/main/spiece.model
4.31 MB
- Xet hash:
- e014fc644c17ceafb530dcbdb2b4f99ac49de1cfddf963448275df9f4b091cde
- Size of remote file:
- 4.31 MB
- SHA256:
- ef78f86560d809067d12bac6c09f19a462cb3af3f54d2b8acbba26e1433125d6
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