Instructions to use recursionpharma/OpenPhenom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use recursionpharma/OpenPhenom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="recursionpharma/OpenPhenom", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("recursionpharma/OpenPhenom", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update RxRx3-core_inference.ipynb
#15
by recursionaut - opened
RxRx3-core_inference.ipynb
CHANGED
|
@@ -30,7 +30,7 @@
|
|
| 30 |
"source": [
|
| 31 |
"# Load model directly\n",
|
| 32 |
"from huggingface_mae import MAEModel\n",
|
| 33 |
-
"open_phenom = MAEModel.from_pretrained(\"
|
| 34 |
]
|
| 35 |
},
|
| 36 |
{
|
|
|
|
| 30 |
"source": [
|
| 31 |
"# Load model directly\n",
|
| 32 |
"from huggingface_mae import MAEModel\n",
|
| 33 |
+
"open_phenom = MAEModel.from_pretrained(\"recursionpharma/OpenPhenom\")"
|
| 34 |
]
|
| 35 |
},
|
| 36 |
{
|