Instructions to use Pawel-M/src_ctx_and_term_nllb_600M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pawel-M/src_ctx_and_term_nllb_600M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Pawel-M/src_ctx_and_term_nllb_600M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Pawel-M/src_ctx_and_term_nllb_600M") model = AutoModel.from_pretrained("Pawel-M/src_ctx_and_term_nllb_600M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Pawel-M/src_ctx_and_term_nllb_600M: direct link, hf CLI and curl.
- Browser
- Download file 17.3 MB
-
https://huggingface.co/Pawel-M/src_ctx_and_term_nllb_600M/resolve/main/tokenizer.json
- Command line
-
hf download hf://Pawel-M/src_ctx_and_term_nllb_600M/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Pawel-M/src_ctx_and_term_nllb_600M/resolve/main/tokenizer.json
17.3 MB
- Xet hash:
- 18761a875b5fe0e2091fe1af33c9d084902f95f0a38d4cdb1d2fa411850a95dd
- Size of remote file:
- 17.3 MB
- SHA256:
- 8ac789ad7dabea44d41537822d48c516ba358374c51813e2cba78c006e150c94
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