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:
# 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
File size: 336 Bytes
a3afa1d d2b84ea a3afa1d | 1 2 3 4 5 6 7 8 9 10 11 12 | """Lazy model-family namespace for FastPLMs.
Model classes are resolved through Transformers AutoClasses and the typed
registry. Importing this package therefore does not load checkpoints, create
tokenizers, compile kernels, or initialize an accelerator runtime.
"""
from __future__ import annotations
__all__: tuple[str, ...] = ()
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