How to run ANY Hugging Face Model in Ollama!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

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AI Summary

Video Summary: Running Quantized GG UF Models Locally with AMA

• Objective: Demonstrate how to run quantized GG UF models from Hugging Face Model Hub locally using AMA with a single command.
• Requirements:
  • AMA must be installed and running on the computer.
  • Access to the terminal to execute commands.

Steps to Run a Model:

1. Download and Install AMA:
   • Ensure AMA is installed and can be executed from the command line interface (CLI).
   • Verify AMA installation by running AMA in the CLI and checking for expected output.
2. Select a Model from Hugging Face Model Hub:
   • Visit the Hugging Face Model Hub and choose a model.
   • For the demo, a smaller model is selected for ease of use, such as the “Grow with Granite” models from IBM.
3. Run the Model Locally:
   • Use the command format: AMA run HF-URL/username/model-name:latest.
   • The command pulls the model directly from Hugging Face Model Hub without needing it on AMA Model Hub.
   • Quantized versions can be specified if needed by appending the version (e.g., Q8) to the command.
4. Model Download and Execution:
   • The model is downloaded, and SHA-256 digests are verified to ensure integrity.
   • Once downloaded, the model can be interacted with, such as asking it to tell a joke.

Additional Information:

• Quantization: A process to reduce model precision while retaining accuracy, known as post-training quantization.
• GG UF Format: A new format popularized by Lama CPP, which is at the core of these advancements.

Example Interaction with the Model:

• The model can respond to prompts such as telling jokes or providing information.

Conclusion:

• The process allows for running various models, including large language and vision-language models.
• Models can also be run as an API endpoint, but that is covered in a different tutorial.
• The key takeaway is the simplicity of running models with a single command line.

(Note: No detailed instructions such as CLI commands, website URLs, or tips were provided in the text to extract.)