Hugging Face Model Hub
Hugging Face Model Hub
Hugging Face offers thousands of pre-trained models on the Model Hub. You can search for models for various tasks (text generation, translation, summarization, etc.) and directly load them with from_pretrained method.
model = AutoModelForSequenceClassification.from_pretrained('distilbert-base-uncased-finetuned-sst-2-english')Fine-tuning Models
You can fine-tune pre-trained models using your own data using the Hugging Face Trainer API. This is a bit more involved, but Hugging Face provides excellent documentation for fine-tuning models for custom tasks. The basic steps are:
- Load your custom dataset
- Tokenize the data
- Create a
Trainerinstance - Train the model
Sharing and Deploying Models
Once you fine-tune a model, you can upload it to the Hugging Face Model Hub to share it with others. You can also deploy models using Hugging Face’s Inference API or use the transformers library to perform inference directly on your server.
Tips
- Explore Datasets: Hugging Face also offers the
datasetslibrary, which is great for loading and working with popular datasets in NLP. You can install it via pip:pip install datasets - Join the Community: Hugging Face has an active and welcoming community. If you’re stuck or want to learn more, you can check out the Hugging Face forums, or explore their tutorials and courses on their website.
