Transformers
Safetensors
t5
text2text-generation
protein-language-model
fastplms
custom_code
text-generation-inference
Instructions to use Synthyra/ANKH_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ANKH_base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Synthyra/ANKH_base", trust_remote_code=True) model = AutoModelForSeq2SeqLM.from_pretrained("Synthyra/ANKH_base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download requirements.txt from Synthyra/ANKH_base: direct link, hf CLI and curl.
- Browser
- Download file 231 Bytes
-
https://huggingface.co/Synthyra/ANKH_base/resolve/main/requirements.txt
- Command line
-
hf download hf://Synthyra/ANKH_base/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/Synthyra/ANKH_base/resolve/main/requirements.txt
231 Bytes
| # Direct runtime dependencies for Synthyra/ANKH_base. | |
| # FastPLMs source is embedded in this model repository. | |
| torch>=2.14 | |
| transformers>=5.17 | |
| huggingface-hub>=1.32 | |
| tokenizers>=0.23 | |
| safetensors>=0.8 | |
| numpy>=2.5 | |
| einops>=0.8 | |
| tqdm>=4.70 | |