
# MedCLIP

## Model description


## Intended uses & limitations

#### How to use

```python
# You can include sample code which will be formatted
```

#### Limitations and bias

Provide examples of latent issues and potential remediations.

## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data.

## Training procedure

Preprocessing, hardware used, hyperparameters...

## Eval results

### BibTeX entry and citation info

```bibtex
@inproceedings{...,
  year={2020}
}
```

{"language": ["en"], "license": "apache-2.0", "tags": ["vision"]}
transformers jax tensorboard hybrid-clip vision en license:apache-2.0 endpoints_compatible has_space region:us
TAGS
#transformers #jax #tensorboard #hybrid-clip #vision #en #license-apache-2.0 #endpoints_compatible #has_space #region-us 


# MedCLIP

## Model description


## Intended uses & limitations

#### How to use



#### Limitations and bias

Provide examples of latent issues and potential remediations.

## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data.

## Training procedure

Preprocessing, hardware used, hyperparameters...

## Eval results

### BibTeX entry and citation info



# MedCLIP ## Model description ## Intended uses & limitations #### How to use #### Limitations and bias

Provide examples of latent issues and potential remediations. ## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data. ## Training procedure

Preprocessing, hardware used, hyperparameters... ## Eval results ### BibTeX entry and citation info
TAGS
#transformers #jax #tensorboard #hybrid-clip #vision #en #license-apache-2.0 #endpoints_compatible #has_space #region-us 
 # MedCLIP ## Model description ## Intended uses & limitations #### How to use #### Limitations and bias

Provide examples of latent issues and potential remediations. ## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data. ## Training procedure

Preprocessing, hardware used, hyperparameters... ## Eval results ### BibTeX entry and citation info
passage: TAGS
#transformers #jax #tensorboard #hybrid-clip #vision #en #license-apache-2.0 #endpoints_compatible #has_space #region-us 
# MedCLIP## Model description## Intended uses & limitations#### How to use#### Limitations and bias

Provide examples of latent issues and potential remediations.## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data.## Training procedure

Preprocessing, hardware used, hyperparameters...## Eval results### BibTeX entry and citation info