Fill-Mask
Transformers
PyTorch
TensorFlow
Safetensors
esm
biology
protein-language-model
proteins
embeddings
drug-discovery
aurigene
Instructions to use Aurigene-AI/esm2_t33_650M_UR50D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aurigene-AI/esm2_t33_650M_UR50D with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Aurigene-AI/esm2_t33_650M_UR50D")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Aurigene-AI/esm2_t33_650M_UR50D") model = AutoModelForMaskedLM.from_pretrained("Aurigene-AI/esm2_t33_650M_UR50D", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Aurigene-AI/esm2_t33_650M_UR50D: direct link, hf CLI and curl.
- Browser
- Download file 2.61 GB
-
https://huggingface.co/Aurigene-AI/esm2_t33_650M_UR50D/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Aurigene-AI/esm2_t33_650M_UR50D/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aurigene-AI/esm2_t33_650M_UR50D/resolve/main/pytorch_model.bin
2.61 GB
- Xet hash:
- ef8077a9a9b7c30da8dfc96075faa08b31738d640abf8529ceeda08e0e4dd036
- Size of remote file:
- 2.61 GB
- SHA256:
- c874668852c7275a159e2c7ceb6069671d7b1ba2c7b52f59600b34ce0f721008
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