
# MyModelName

## Model description

Describe the model here (what it does, what it's used for, etc.)

## 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

## Generated Images

You can embed local or remote images using `![](...)`

### BibTeX entry and citation info

```bibtex
@inproceedings{...,
  year={2020}
}
```
{"license": "mit", "tags": ["huggan", "gan"]}
transformers pytorch gpt2 text-generation huggan gan license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #huggan #gan #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# MyModelName

## Model description

Describe the model here (what it does, what it's used for, etc.)

## 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

## Generated Images

You can embed local or remote images using '![](...)'

### BibTeX entry and citation info


# MyModelName ## Model description

Describe the model here (what it does, what it's used for, etc.) ## 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 ## Generated Images

You can embed local or remote images using '![](...)' ### BibTeX entry and citation info
TAGS
#transformers #pytorch #gpt2 #text-generation #huggan #gan #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # MyModelName ## Model description

Describe the model here (what it does, what it's used for, etc.) ## 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 ## Generated Images

You can embed local or remote images using '![](...)' ### BibTeX entry and citation info
passage: TAGS
#transformers #pytorch #gpt2 #text-generation #huggan #gan #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# MyModelName## Model description

Describe the model here (what it does, what it's used for, etc.)## 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## Generated Images

You can embed local or remote images using '![](...)'### BibTeX entry and citation info