AmelieSchreiber
commited on
Commit
·
3db1969
1
Parent(s):
1e414d1
Update README.md
Browse files
README.md
CHANGED
@@ -43,6 +43,15 @@ dataset [found here](https://huggingface.co/datasets/AmelieSchreiber/binding_sit
|
|
43 |
this model has a high recall, meaning it is likely to detect binding sites, but it has a precision score that is somewhat lower than the SOTA
|
44 |
structural models mentioned above, meaning the model may return some false positives as well.
|
45 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
46 |
## Training procedure
|
47 |
|
48 |
This model was finetuned with LoRA on ~549K protein sequences from the UniProt database. The dataset can be found
|
|
|
43 |
this model has a high recall, meaning it is likely to detect binding sites, but it has a precision score that is somewhat lower than the SOTA
|
44 |
structural models mentioned above, meaning the model may return some false positives as well.
|
45 |
|
46 |
+
|
47 |
+
## Running Inference
|
48 |
+
|
49 |
+
You can download and run [this notebook](https://huggingface.co/AmelieSchreiber/esm2_t12_35M_lora_binding_sites_v2_cp3/blob/main/testing_and_inference.ipynb)
|
50 |
+
to test out any of the ESMB models. Note, if you would like to run the models on the train/test split to get the metrics, you may need to do
|
51 |
+
locally or in a Colab Pro instance as the datasets are quite large and will not run in a standard Colab (you can still run inference on your own
|
52 |
+
protein sequences though).
|
53 |
+
|
54 |
+
|
55 |
## Training procedure
|
56 |
|
57 |
This model was finetuned with LoRA on ~549K protein sequences from the UniProt database. The dataset can be found
|