Model Details
Full Model IDbiohub/ESMC-6B
Pipeline / Taskfill-mask
Librarytransformers
Downloads (all-time)2.0M
Likes27
Last Modified6/3/2026
Author / Orgbiohub
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("fill-mask", model="biohub/ESMC-6B")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsesmcfill-maskbiologyesmproteinprotein-language-modelprotein-embeddingsmasked-language-modelingtransfer-learningvariant-effect-predictionprotein-engineeringenlicense:mitlicense:otherendpoints_compatibleregion:us
More fill-mask Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: fill-mask
This model is designed for the fill-mask task. Explore more models for this use case.
All fill-mask Models →📊 Popularity
⬇ Downloads2.0M
❤️ Community Likes27
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.