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")# 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 generation_config.json from ElnaggarLab/ankh3-xl: direct link, hf CLI and curl.
- Browser
- Download file 142 Bytes
-
https://huggingface.co/ElnaggarLab/ankh3-xl/resolve/2f29d5f019e6cc20627b4ce2cb81e2dc6b4a80e7/generation_config.json
- Command line
-
hf download hf://ElnaggarLab/ankh3-xl@2f29d5f019e6cc20627b4ce2cb81e2dc6b4a80e7/generation_config.json
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curl -L -o generation_config.json https://huggingface.co/ElnaggarLab/ankh3-xl/resolve/2f29d5f019e6cc20627b4ce2cb81e2dc6b4a80e7/generation_config.json
142 Bytes
| { | |
| "_from_model_config": true, | |
| "decoder_start_token_id": 0, | |
| "eos_token_id": 1, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.26.1" | |
| } | |