
# SetFit StaQT

This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:

1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
2. Training a classification head with features from the fine-tuned Sentence Transformer.

## Usage

To use this model for inference, first install the SetFit library:

```bash
python -m pip install setfit
```

You can then run inference as follows:

```python
from setfit import SetFitModel

# Download from Hub and run inference
model = SetFitModel.from_pretrained("koutch/setfit_staqt")
# Run inference

```

{"license": "apache-2.0", "tags": ["setfit", "sentence-transformers", "text-classification"], "pipeline_tag": "text-classification"}
sentence-transformers pytorch deberta-v2 setfit text-classification license:apache-2.0 region:us
TAGS
#sentence-transformers #pytorch #deberta-v2 #setfit #text-classification #license-apache-2.0 #region-us 


# SetFit StaQT

This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:

1. Fine-tuning a Sentence Transformer with contrastive learning.
2. Training a classification head with features from the fine-tuned Sentence Transformer.

## Usage

To use this model for inference, first install the SetFit library:



You can then run inference as follows:



# SetFit StaQT

This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:

1. Fine-tuning a Sentence Transformer with contrastive learning.
2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Usage

To use this model for inference, first install the SetFit library:



You can then run inference as follows:
TAGS
#sentence-transformers #pytorch #deberta-v2 #setfit #text-classification #license-apache-2.0 #region-us 
 # SetFit StaQT

This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:

1. Fine-tuning a Sentence Transformer with contrastive learning.
2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Usage

To use this model for inference, first install the SetFit library:



You can then run inference as follows:
TAGS
#sentence-transformers #pytorch #deberta-v2 #setfit #text-classification #license-apache-2.0 #region-us 
# SetFit StaQT

This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:

1. Fine-tuning a Sentence Transformer with contrastive learning.
2. Training a classification head with features from the fine-tuned Sentence Transformer.## Usage

To use this model for inference, first install the SetFit library:



You can then run inference as follows: