Spacy Explosion argilla arxiv:1910.09700 region:us
---
library_name: Spacy Explosion
tags:
- argilla
---

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# Model Card for *Model ID*

This model has been created with [Argilla](https://docs.argilla.io), trained with *Spacy Explosion*.

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## Model training

Training the model using the `ArgillaTrainer`:

```python
# Load the dataset:
dataset = FeedbackDataset.from_argilla("...")

# Create the training task:
def formatting_func(sample):
    text = sample["text"]
    label = sample["label"][0]["value"]
    return(text, label)

task = TrainingTask.for_text_classification(formatting_func=formatting_func)

# Create the ArgillaTrainer:
trainer = ArgillaTrainer(
    dataset=dataset,
    task=task,
    framework="spacy",
    lang="en",
    gpu_id=-1,
    framework_kwargs={'optimize': 'efficiency', 'freeze_tok2vec': False},
)

trainer.train(output_dir="None")
```

You can test the type of predictions of this model like so:

```python
trainer.predict("This is awesome!")
```

## Model Details

### Model Description

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- **Developed by:** [More Information Needed]
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## Training Details

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### Training Hyperparameters

- **Training regime:** (fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision)
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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

### Framework Versions

- Python: 3.9.19
- Argilla: 1.29.0

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