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---
language:
- "en"
thumbnail: "https://example.com/path/to/your/thumbnail.jpg" # URL to a thumbnail used in social sharing
tags:
- "tag1" # For example, "sentiment-analysis"
- "tag2" # For example, "machine-translation"
license: "mit"
datasets:
- "dataset1" # For example, "imdb"
- "dataset2" # For example, "wmt16"
metrics:
- "metric1" # For example, "accuracy"
- "metric2" # For example, "f1"
---
# Your Model Name
## Introduction
This is a brief introduction about your transformer-based model. Here, you can mention the type of the model, the task it was trained for, its performance, and other key features or highlights.
## Training
Here, give detailed information about how the model was trained:
- Dataset(s) used for training
- Preprocessing techniques used
- Training configuration such as the batch size, learning rate, optimizer, number of epochs, etc.
- Any specific challenges or notable aspects of the training process
## Usage
Provide examples of how to use the model for inference. You can provide both a simple usage case and a more complex one if necessary. Make sure to explain what the inputs and outputs are.
Here's a basic example:
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("your-model-name")
model = AutoModel.from_pretrained("your-model-name")
inputs = tokenizer("Your example sentence", return_tensors="pt")
outputs = model(**inputs)
# Explain what the outputs are
## Evaluation
Discuss how the model was evaluated, which metrics were used, and what results it achieved.
## Limitations and Bias
Every model has its limitations and may have certain biases due to the data it was trained on. Explain those here.
## About Us
A small introduction about you or your team.
## Acknowledgments
Thank people, organizations or mention the resources that helped you in this work.
## License
This model is distributed under the MIT license.
## Contact
Provide a contact method (e.g., email or GitHub issues) for people to reach out with questions, comments, or concerns.
## References
List any relevant references for your model here. |