Feature Extraction
Transformers
Safetensors
protenrich
proteins
bioinformatics
drug-discovery
custom_code
Instructions to use SaeedLab/ProtEnrich-Ankh3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/ProtEnrich-Ankh3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/ProtEnrich-Ankh3", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaeedLab/ProtEnrich-Ankh3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 592 Bytes
e039883 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | from transformers import PretrainedConfig
class ProtEnrichConfig(PretrainedConfig):
model_type = "protenrich"
def __init__(
self,
seq_dim : int = 2560,
struct_dim: int = 1024,
dyn_dim: int = 20,
embed_dim: int = 1024,
project_dim: int = 256,
alpha_max: float = 0.3,
num_labels: int = 2,
**kwargs):
super().__init__(**kwargs)
self.seq_dim = seq_dim
self.struct_dim = struct_dim
self.dyn_dim = dyn_dim
self.embed_dim = embed_dim
self.project_dim = project_dim
self.alpha_max = alpha_max
self.num_labels = num_labels |