Feature Extraction
Transformers
Safetensors
fast_esm3
biology
protein-language-model
esm3
multimodal-protein-model
custom_code
Instructions to use Synthyra/ESM3_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESM3_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/ESM3_small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Synthyra/ESM3_small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 539 Bytes
eb90d52 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"architectures": [
"FastESM3Model"
],
"attn_backend": "sdpa",
"auto_map": {
"AutoConfig": "modeling_esm3.FastESM3Config",
"AutoModel": "modeling_esm3.FastESM3Model",
"AutoModelForMaskedLM": "modeling_esm3.FastESM3Model"
},
"hidden_size": 1536,
"initializer_range": 0.02,
"model_name": "esm3_sm_open_v1",
"model_type": "fast_esm3",
"num_attention_heads": 24,
"num_hidden_layers": 48,
"num_vector_heads": 256,
"tie_word_embeddings": false,
"transformers_version": "4.57.6",
"vocab_size": 64
}
|