1. Tailorable prompts to meet your specific requirements 2. Constructing chain link components for advanced usage scenarios 3. Integrating models for data augmentation and accessing top-notch language model capabilities, such as GPT and HuggingFace Hub. 4. Versatile components that allow mixing and mat...
Step 1: https://huggingface.co/spaces Go to https://huggingface.co/spaces and click “Create new Space”Step 2: Create a new space Give it a “Space name”. Here I call it “panel_example”. Select Docker as the Space SDK, and then click “Create Space”.Step...
First, log in to the Hugging Face Hub. You will need to create awritetoken in yourAccount Settings. Then there are two options to log in: Typehuggingface-cli loginin your terminal and enter your token. If in a python notebook, you can usenotebook_login. fromhuggingface...
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Note how all the implementation details are under the cover of the TinyLlama class, and the end user doesn’t need to know how to actually install the model into Ollama, what GGUF is, or that to get huggingface-cli you need to pip install huggingface-hub. Advantages of this appro...
fromhuggingface_hubimportnotebook_login notebook_login() You will be prompted to enter your Hugging Face access token. If you don’t have one, you can create oneon the Hugging Face website. Importing Required Dependencies We now import the required dependencies, which include diffusers, StableDi...
importosfromhuggingface_hubInferenceClient# Initialize the client with your deployed endpoint and bearer tokenclient=InferenceClient(base_url="http://localhost:8080"api_keygetenv Step 3: Prepare Batch Inputs # Create a list of inputsbatch_inputs=[{"role""user"] ...
Step 1: Install the required libraries We will require the following libraries for this tutorial: datasets: Python library to get access to datasets available on Hugging Face Hub ragas: Python library for the RAGAS framework langchain: Python library to develop LLM applications using LangChain lang...
Step 1: Install the required libraries We will require the following libraries for this tutorial: datasets: Python library to get access to datasets available on Hugging Face Hub ragas: Python library for the RAGAS framework langchain: Python library to develop LLM applications using LangChain lang...
pip install -U autotrain-advanced Also, we would use the Alpaca sample dataset fromHuggingFace, which required datasets package to acquire. pip install datasets Then, use the following code to acquire the data we need. from datasets import load_dataset ...