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
Commit History
12 days ago
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Update FastPLMs files from Synthyra/FastPLMs 32d9951 (PR 52: ESMFold2 noise cap, DPLM2 parity)
Verified signature78db51f
29 days ago
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Apply coding standards from 1cb5747 (files only)
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Update FastPLMs runtime and cards from 328deef (files only)
Verified signature4219856
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Update FastPLMs runtime and model cards
Verified signatureAdd-only FastPLMs files-only publication. Checkpoint weights and complete-artifact attestations are unchanged.d2b84ea
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Update FastPLMs runtime files
Verified signatureAtomic FastPLMs complete publication. Checkpoint weights, tokenizer assets, runtime sources, model card, legal texts, and scoped attestations are updated together. Deletes are restricted to obsolete current-registry-pinned paths.a3afa1d