Transformers
Safetensors
English
esmfold2
biology
esm
protein
protein-structure-prediction
structure-prediction
protein-design
3d-structure
confidence-estimation
molecular-dynamics
Instructions to use biohub/ESMFold2-Fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biohub/ESMFold2-Fast with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("biohub/ESMFold2-Fast", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,338 Bytes
b732f7a e5d5874 b732f7a 3e57ae6 b732f7a e5d5874 b732f7a e5d5874 b732f7a e5d5874 3e57ae6 b732f7a 535c0f7 b732f7a 3e57ae6 b732f7a 535c0f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | {
"architectures": [
"ESMFold2Model"
],
"confidence_head": {
"distogram_bins": 39,
"enabled": true,
"folding_trunk": {
"dropout": 0.25,
"n_heads": 8,
"n_layers": 4
},
"max_dist": 50.75,
"min_dist": 3.25,
"num_pae_bins": 64,
"num_pde_bins": 64,
"num_plddt_bins": 50
},
"d_pair": 256,
"d_single": 384,
"disable_msa_features": false,
"dtype": "float32",
"esmc_id": "biohub/ESMC-6B",
"folding_trunk": {
"dropout": 0.25,
"n_heads": 8,
"n_layers": 24
},
"force_lm_dropout_during_inference": false,
"inputs": {
"atom_encoder": {
"d_atom": 128,
"d_token": 768,
"expansion_ratio": 2,
"n_blocks": 3,
"n_heads": 4,
"n_spatial_rope_pairs_per_axis": 2,
"n_uid_rope_pairs": 10,
"spatial_rope_base_frequency": 20.0,
"swa_window_size": 128,
"uid_rope_base_frequency": 10000.0
},
"d_inputs": 451
},
"lm_d_model": 2560,
"lm_dropout": 0.0,
"lm_encoder": {
"enabled": true,
"lm_dropout": 0.25,
"n_layers": 4,
"per_loop_lm_dropout": true
},
"lm_num_layers": 80,
"model_type": "esmfold2",
"msa_encoder": {
"d_hidden": 32,
"d_msa": 128,
"enabled": false,
"msa_head_width": 32,
"n_heads_msa": 8,
"n_layers": 4
},
"msa_encoder_overwrite": true,
"n_relative_chain_bins": 2,
"n_relative_residx_bins": 32,
"num_diffusion_samples": 32,
"num_loops": 3,
"parcae": {
"coda_n_layers": 2,
"enabled": true,
"max_steps": 6,
"min_steps": 1,
"poisson_mean": 3.0
},
"structure_head": {
"diffusion_module": {
"atom_num_blocks": 3,
"atom_num_heads": 4,
"c_atom": 128,
"c_s_inputs": 451,
"c_token": 768,
"c_z": 256,
"fourier_dim": 256,
"relpos_r_max": 32,
"relpos_s_max": 2,
"sigma_data": 16.0,
"token_num_blocks": 12,
"token_num_heads": 16,
"transition_multiplier": 2
},
"distogram_bins": 64,
"gamma_0": 0.8,
"gamma_min": 1.0,
"inference_num_steps": 14,
"inference_p": 7.0,
"inference_s_max": 160.0,
"inference_s_min": 0.0004,
"noise_scale": 1.003,
"step_scale": 1.5,
"train_noise_log_mean": -1.2,
"train_noise_log_std": 1.5
},
"transformers_version": "4.57.6",
"type": "release"
} |