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-Experimental-Fast-base300M-step1500k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biohub/ESMFold2-Experimental-Fast-base300M-step1500k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("biohub/ESMFold2-Experimental-Fast-base300M-step1500k") model = AutoModel.from_pretrained("biohub/ESMFold2-Experimental-Fast-base300M-step1500k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- config.json +1 -1
- model.safetensors +2 -2
config.json
CHANGED
|
@@ -57,7 +57,7 @@
|
|
| 57 |
"n_relative_chain_bins": 2,
|
| 58 |
"n_relative_residx_bins": 32,
|
| 59 |
"num_diffusion_samples": 16,
|
| 60 |
-
"
|
| 61 |
"structure_head": {
|
| 62 |
"diffusion_module": {
|
| 63 |
"atom_num_blocks": 3,
|
|
|
|
| 57 |
"n_relative_chain_bins": 2,
|
| 58 |
"n_relative_residx_bins": 32,
|
| 59 |
"num_diffusion_samples": 16,
|
| 60 |
+
"num_loops": 3,
|
| 61 |
"structure_head": {
|
| 62 |
"diffusion_module": {
|
| 63 |
"atom_num_blocks": 3,
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:44d6797c5efebf24753d502b40950e0874871c96ceea14f2d7f7e39cebac67fd
|
| 3 |
+
size 684606540
|