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README.md

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+---
+library_name: Transformers
+tags:
+- text-classification
+- transformers
+- argilla
+---
+
+<!-- This model card has been generated automatically according to the information the `ArgillaTrainer` had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Model Card for *Model ID*
+
+This model has been created with [Argilla](https://docs.argilla.io), trained with *Transformers*.
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## 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="transformers",
+    model="bert-base-cased",
+)
+
+trainer.update_config({
+    "evaluation_strategy": "epoch",
+    "logging_dir": "./logs",
+    "logging_steps": 1,
+    "num_train_epochs": 1,
+    "output_dir": "textcat_model_transformers",
+    "use_mps_device": true
+})
+
+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
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+<!--
+## Uses
+
+*Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model.*
+-->
+
+<!--
+### Direct Use
+
+*This section is for the model use without fine-tuning or plugging into a larger ecosystem/app.*
+-->
+
+<!--
+### Downstream Use [optional]
+
+*This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app*
+-->
+
+<!--
+### Out-of-Scope Use
+
+*This section addresses misuse, malicious use, and uses that the model will not work well for.*
+-->
+
+<!--
+## Bias, Risks, and Limitations
+
+*This section is meant to convey both technical and sociotechnical limitations.*
+-->
+
+<!--
+### Recommendations
+
+*This section is meant to convey recommendations with respect to the bias, risk, and technical limitations.*
+-->
+
+<!--
+## Training Details
+
+### Training Metrics
+
+*Metrics related to the model training.*
+-->
+
+<!--
+### Training Hyperparameters
+
+- **Training regime:** (fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision)
+-->
+
+<!--
+## Environmental Impact
+
+*Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly*
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+-->
+
+## Technical Specifications [optional]
+
+### Framework Versions
+
+- Python: 3.9.17
+- Argilla: 1.21.0-dev
+
+<!--
+## Citation [optional]
+
+*If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section.*
+
+### BibTeX
+-->
+
+<!--
+## Glossary [optional]
+
+*If relevant, include terms and calculations in this section that can help readers understand the model or model card.*
+-->
+
+<!--
+## Model Card Authors [optional]
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->