Instructions to use ElnaggarLab/ankh3-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElnaggarLab/ankh3-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ElnaggarLab/ankh3-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ElnaggarLab/ankh3-large") model = AutoModelForSeq2SeqLM.from_pretrained("ElnaggarLab/ankh3-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ElnaggarLab/ankh3-large: direct link, hf CLI and curl.
- Browser
- Download file 7.52 GB
-
https://huggingface.co/ElnaggarLab/ankh3-large/resolve/0ccbf43802c44eb5edfb6ce1fcb98959382ed9cf/model.safetensors
- Command line
-
hf download hf://ElnaggarLab/ankh3-large@0ccbf43802c44eb5edfb6ce1fcb98959382ed9cf/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ElnaggarLab/ankh3-large/resolve/0ccbf43802c44eb5edfb6ce1fcb98959382ed9cf/model.safetensors
7.52 GB
- Xet hash:
- 50b3ff2f738e653588c4e3691f258760fbf2ec05a50bd6a403ddec45206d6e5d
- Size of remote file:
- 7.52 GB
- SHA256:
- 2adb8f66712c0ac3d8051e79ce4166dc1e0a5bcab03a2b0fb38cbf0837465c52
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