Instructions to use Synthyra/ESM2-8M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESM2-8M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/ESM2-8M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/ESM2-8M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download fastplms/kernels.lock from Synthyra/ESM2-8M: direct link, hf CLI and curl.
- Browser
- Download file 4.72 kB
-
https://huggingface.co/Synthyra/ESM2-8M/resolve/main/fastplms/kernels.lock
- Command line
-
hf download hf://Synthyra/ESM2-8M/fastplms/kernels.lock
-
curl -L -o kernels.lock https://huggingface.co/Synthyra/ESM2-8M/resolve/main/fastplms/kernels.lock
4.72 kB
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