Instructions to use ElnaggarLab/ankh3-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElnaggarLab/ankh3-xl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ElnaggarLab/ankh3-xl")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ElnaggarLab/ankh3-xl") model = AutoModelForSeq2SeqLM.from_pretrained("ElnaggarLab/ankh3-xl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model-00003-of-00003.bin from ElnaggarLab/ankh3-xl: direct link, hf CLI and curl.
- Browser
- Download file 6.95 GB
-
https://huggingface.co/ElnaggarLab/ankh3-xl/resolve/main/pytorch_model-00003-of-00003.bin
- Command line
-
hf download hf://ElnaggarLab/ankh3-xl/pytorch_model-00003-of-00003.bin
-
curl -L -o pytorch_model-00003-of-00003.bin https://huggingface.co/ElnaggarLab/ankh3-xl/resolve/main/pytorch_model-00003-of-00003.bin
6.95 GB
- Xet hash:
- f0d5658987ca51824a7bfa83ebcff7c8df8ff8a5d5afb5a9b161b88b5f3a0a45
- Size of remote file:
- 6.95 GB
- SHA256:
- 055a853bdd3623db95a637935aa299427e837cd8ea69fc04708b0262508bec75
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