Feature Extraction
Transformers
Safetensors
protenrich
proteins
bioinformatics
drug-discovery
custom_code
Instructions to use SaeedLab/ProtEnrich-CARP-640M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaeedLab/ProtEnrich-CARP-640M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SaeedLab/ProtEnrich-CARP-640M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SaeedLab/ProtEnrich-CARP-640M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
1953026
1
Parent(s): efc1d81
update
Browse files- modeling_protenrich.py +1 -1
modeling_protenrich.py
CHANGED
|
@@ -9,7 +9,7 @@ from transformers import PreTrainedModel
|
|
| 9 |
from transformers.modeling_outputs import BaseModelOutputWithPooling, SequenceClassifierOutput
|
| 10 |
from transformers import AutoModel
|
| 11 |
|
| 12 |
-
from configuration_protenrich import ProtEnrichConfig
|
| 13 |
|
| 14 |
@dataclass
|
| 15 |
class ProtEnrichModelOutput(ModelOutput):
|
|
|
|
| 9 |
from transformers.modeling_outputs import BaseModelOutputWithPooling, SequenceClassifierOutput
|
| 10 |
from transformers import AutoModel
|
| 11 |
|
| 12 |
+
from .configuration_protenrich import ProtEnrichConfig
|
| 13 |
|
| 14 |
@dataclass
|
| 15 |
class ProtEnrichModelOutput(ModelOutput):
|