This container houses the Llama3.1-Typhoon2-70b-Instruct, an instruction-tuned LLM by SCB 10X & VISTEC. Fine-tuned from Meta's Llama 3.1-70B, it excels in complex generative and conversational tasks for both Thai and English.
Llama3.1-Typhoon2-70B-Instruct Overview
Description:
This container houses the Llama3.1-Typhoon2-70b-Instruct is an advanced, instruction-tuned large language model engineered for superior performance in both Thai and English. Developed through a collaboration between SCB 10X and VISTEC, this model is a specialized fine-tuning of Meta's foundational Llama 3.1-70B architecture, optimized to adeptly handle a diverse spectrum of complex generative and conversational tasks.
The container components are ready for commercial/non-commercial use.
Third-Party Community Consideration
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[scb10x/llama3.1-typhoon2-70b-instruct]
(scb10x/llama3.1-typhoon2-70b-instruct · Hugging Face).
License/Terms of Use:
GOVERNING TERMS: The NIM container is governed by the NVIDIA Software License Agreement and the Product-Specific Terms for NVIDIA AI Products. The model is governed by the NVIDIA Community Model License Agreement;
ADDITIONAL INFORMATION: Llama 3.1 Community License. Built with Llama.
You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.
Deployment Geography:
Global
Release Date:
Huggingface 07/19/2024 via
scb10x/llama3.1-typhoon2-70b-instruct · Hugging Face
Llama3.1-Typhoon2-70b-Instruct
Llama3.1-Typhoon2-70b-Instruct Container includes the following model:
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| Llama3.1-Typhoon2-70b-Instruct | The primary, full-precision model for high-quality text generation, research, or further fine-tuning. Lighter versions optimized for specific hardware. AWQ is for fast inference on NVIDIA GPUs, while GGUF is for running on CPUs. | Automatic |
Deployment Details:
Visit the NIM Container LLM page for release documentation, deployment guides, and more.
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.
Container Version(s):
nvcr.io/nvstaging/nim/llama-3.1-typhoon2-70b-instruct:1.10.1-32129505
Ethical Considerations:
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal developer team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
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You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws
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