@@ -497,7 +497,9 @@ If you want your model to be namespaced by your organization name rather than yo
...
@@ -497,7 +497,9 @@ If you want your model to be namespaced by your organization name rather than yo
Your model will then be accessible through its identifier, a concatenation of your username (or organization name) and the folder name above:
Your model will then be accessible through its identifier, a concatenation of your username (or organization name) and the folder name above:
```python
```python
"namespace/pretrained_model"
"username/pretrained_model"
# or if an org:
"organization_name/pretrained_model"
```
```
**Please add a README.md model card** to the repo under `model_cards/` with: model description, training params (dataset, preprocessing, hardware used, hyperparameters), evaluation results, intended uses & limitations, etc.
**Please add a README.md model card** to the repo under `model_cards/` with: model description, training params (dataset, preprocessing, hardware used, hyperparameters), evaluation results, intended uses & limitations, etc.
@@ -28,7 +28,9 @@ If you want your model to be namespaced by your organization name rather than yo
...
@@ -28,7 +28,9 @@ If you want your model to be namespaced by your organization name rather than yo
Your model will then be accessible through its identifier, a concatenation of your username (or organization name) and the folder name above:
Your model will then be accessible through its identifier, a concatenation of your username (or organization name) and the folder name above:
```python
```python
"namespace/pretrained_model"
"username/pretrained_model"
# or if an org:
"organization_name/pretrained_model"
```
```
**Please add a README.md model card** to the repo under `model_cards/` with: model description, training params (dataset, preprocessing, hardware used, hyperparameters), evaluation results, intended uses & limitations, etc.
**Please add a README.md model card** to the repo under `model_cards/` with: model description, training params (dataset, preprocessing, hardware used, hyperparameters), evaluation results, intended uses & limitations, etc.