Getting started with Hugging Face Transformers is the first step toward building state-of-the-art AI applications in natural language processing (NLP), computer vision, and audio. Whether you need to install the library or download specific pre-trained models for offline use, this guide covers every method available. 1. How to Install the Transformers Library
For the absolute latest features (which may be unstable), you can install directly from the Transformers GitHub repository: pip install git+https://github.com/huggingface/transformers Use code with caution. 2. Downloading Models for Python Projects hugging face transformers download
](https://huggingface.co/models), find your model, and click the **Files and versions** tab to download individual files (like `config.json` and `pytorch_model.bin`). * **Snapshot Download:** Use the `snapshot_download` function from the `huggingface_hub` library to download an entire repository at once. * **Local Loading:** Once downloaded, point your script to the local folder: ```python from transformers import AutoModel model = AutoModel.from_pretrained("./my-model-folder") ``` ### 5. Managing Your Download Cache By default, Hugging Face saves all downloaded models to a hidden cache folder: * **Linux/Mac:** `~/.cache/huggingface/hub/` * **Windows:** `C:\Users\username\.cache\huggingface\hub\` You can change this location by setting the `HF_HOME` or `TRANSFORMERS_CACHE` environment variables if you are running low on disk space. Would you like a specific example of how to download and use a **Large Language Model (LLM)** like Llama or Mistral? Use code with caution. Installation - Hugging Face Getting started with Hugging Face Transformers is the
Note: You must also have a deep learning backend installed, such as PyTorch, TensorFlow, or Flax . conda install -c huggingface transformers ``` Use code with caution. How to Install the Transformers Library For the
Once the library is installed, you can download models directly within your Python scripts using the from_pretrained method. This method automatically downloads the model weights, configuration, and tokenizer files.
from transformers import pipeline # This automatically downloads the default model for sentiment analysis classifier = pipeline("sentiment-analysis") result = classifier("Hugging Face makes AI accessible!") print(result) ``` ### 3. Using the Hugging Face CLI for Direct Downloads For users who want to download entire model repositories without writing a script, the [Hugging Face CLI](https://huggingface.co) is the most efficient tool. 1. **Install the CLI:** `pip install huggingface_hub` 2. **Download a Model:** ```bash huggingface-cli download --local-dir ./my-model-folder ``` ### 4. Downloading for Offline Use If you are working in an environment without internet access, you must download the files ahead of time. * **Manual Download:** Visit the [ Use code with caution. Hugging Face Model Hub Use code with caution.
The most common way to get started is by installing the library via or conda . It is highly recommended to use a virtual environment to avoid package conflicts. Using pip: pip install transformers Use code with caution.