Nemotron 70B Instruct - Details

Nemotron 70B Instruct is a large language model developed by Nvidia, featuring 70 billion parameters. It operates under the Llama 31 Acceptable Use Policy (Llama-31-AUP) and Llama 31 Community License Agreement (LLAMA-31-CCLA). Designed for instruct tasks, the model prioritizes helpfulness and aligns closely with human preferences, making it suitable for a wide range of applications requiring nuanced and user-centric responses.

Nemotron 70B Instruct is a large language model developed by Nvidia with 70 billion parameters and released under the Llama 31 Acceptable Use Policy (Llama-31-AUP) and Llama 31 Community License Agreement (LLAMA-31-CCLA). It is specifically designed to enhance the helpfulness of responses to user queries, achieving high scores on benchmarks such as Arena Hard (85.0), AlpacaEval 2 LC (57.6), and GPT-4-Turbo MT-Bench (8.98). The model is trained using RLHF (Reinforcement Learning from Human Feedback) with specialized methods, focusing on general-domain instruction following while not being optimized for highly specialized areas like math. Its alignment with human preferences makes it well-suited for tasks requiring nuanced, user-centric interactions.

Nemotron 70B Instruct features 70 billion parameters, placing it in the very large models category, which excels at complex tasks but demands significant computational resources. Its 128k context length enables handling extremely long texts, though this requires substantial memory and processing power. The 70b parameter size ensures robust performance across diverse tasks, while the 128k context length allows for detailed analysis of extended inputs, making it suitable for applications requiring deep contextual understanding.

• Parameter Size: 70b (Very Large Models: Best for complex tasks, resource-intensive)
• Context Length: 128k (Very Long Contexts: Ideal for very long texts, highly resource-intensive)

Nemotron 70B Instruct is a large language model designed for text generation, question answering, and code completion, with possible applications in areas like content creation, interactive dialogue systems, or software development assistance. Its 70b parameter size and 128k context length suggest it could handle complex tasks requiring deep contextual understanding, but possible uses in these domains would need rigorous testing to ensure alignment with specific requirements. Possible scenarios might include generating detailed documentation, assisting with coding challenges, or crafting tailored responses to user queries, though these possible applications remain unverified and require further exploration. The model’s focus on helpfulness and human alignment could make it a possible tool for tasks where nuanced, user-centric interactions are valued, but its effectiveness in real-world settings would depend on careful evaluation.

• text generation
• question answering
• code completion

Nemotron 70B Instruct is a large language model with 70 billion parameters and a 128k context length, making it a possible candidate for tasks requiring deep contextual understanding and complex reasoning. Possible applications include generating detailed creative content, such as narratives or technical documentation, where possible use cases might involve drafting reports or crafting engaging stories. It could also serve as a possible tool for interactive dialogue systems, offering possible support in scenarios like virtual assistants or educational platforms. Additionally, possible uses in code generation or software development assistance might leverage its ability to handle extended contexts and intricate instructions. However, these possible applications require thorough evaluation to ensure alignment with specific needs and ethical considerations.

• text generation
• question answering
• code completion
• interactive dialogue systems

Nemotron 70B Instruct in its medium q4 version requires at least 48GB of VRAM across multiple GPUs, with system memory of 32GB or more and adequate cooling to handle the computational load. This quantization balances precision and performance but demands high-end hardware for efficient operation. Available quantized versions: fp16, q2, q3, q4, q5, q6, q8.

Nemotron 70B Instruct is a large language model with 70 billion parameters and a 128k context length, designed for helpfulness and human alignment while operating under the Llama 31 Acceptable Use Policy (Llama-31-AUP) and Llama 31 Community License Agreement (LLAMA-31-CCLA). It excels in general-domain instruction following and nuanced user interactions, making it suitable for text generation, question answering, and code completion tasks.

Huggingface Model Page
Ollama Model Page