Linux / arm64
Linux / amd64
This container houses the Llama-3.2-1B-Instruct, which is an instruction-tuned language model from Meta AI designed to follow user prompts and generate helpful, conversational responses. As a 1 billion parameter model, it's a highly efficient and compact member of the Llama 3.2 family, optimized for a balance of performance and accessibility across a wide range of hardware. It's specifically fine-tuned for dialogue-based applications, making it adept at tasks like question answering, summarization, and other instruction-following scenarios.
The container components are ready for commercial/non-commercial use.
This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA [meta-llama/Llama-3.2-1B-Instruct]
(meta-llama/Llama-3.2-1B-Instruct · Hugging Face).
GOVERNING TERMS: The NIM container is governed by the NVIDIA Software License Agreement and the Product-Specific Terms for NVIDIA AI Products; and the use of the model is governed by the NVIDIA AI Foundation Models Community License Agreement.
ADDITIONAL INFORMATION: Llama 3.2 Community License Agreement. Build with Llama.
You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.
Global
Build.Nvidia.com 09/25/2024 via
llama-3.2-1b-instruct Model by Meta | NVIDIA NIM
Hugging Face 09/25/2024 via
meta-llama/Llama-3.2-1B-Instruct · Hugging Face
NGC 09/25/2024 via
https://catalog.ngc.nvidia.com/orgs/nim/teams/meta/containers/llama-3.2-1b-instruct
Llama-3.2-1B-Instruct Container includes the following model:
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| Llama-3.2-1B-Instruct | A compact, efficient model for conversational AI, including chatbots, question-answering, and content creation. | Automatic |
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Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.
Llama-3.2-1B-Instruct-1.12.0
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