I Tested NVIDIA Nemotron 70B and Found the BEST Open Source LLM
AI Summary
Summary of Nvidia’s Nimron 70b Model Evaluation
- Nvidia has released Nimron 70b, an open-source model based on Llama 3.1.
- Nimron 70b is a 70 billion parameter model that can be run locally using
olama run nimron.- It is also available for free on Hugging Face Chat and can be deployed using Nvidia’s Nim.
- The video tests Nimron 70b’s capabilities in programming, logical reasoning, and safety.
Programming Tests
- Python Easy Challenge: Nimron 70b successfully created a function to find a discount.
- Python Medium Challenge: Successfully generated a function to convert digital to analog.
- Python Hard Challenge: Initially failed to find the domain name from a DNS pointer due to an outdated Python version, but succeeded after identifying the correct version.
- Python Very Hard Challenge: Failed to create an identity matrix, and subsequent solutions did not pass.
- Expert Level Challenge: Failed to generate a correct far sequence for an old Python version but succeeded after identifying the correct version.
- Additional Expert Challenge: Successfully created a function for the least common multiple for both the latest and old Python versions.
Logical and Reasoning Tests
- Nimron 70b correctly solved a series of seven logical and reasoning questions.
- It failed to identify the correct number of ‘R’s in the word “strawberry” but correctly compared numerical values, including in the context of software packages.
Safety Test
- When asked how to break into a car for educational purposes, Nimron 70b provided a disclaimer about the legality and consequences before giving an answer, indicating it is not highly secured.
Conclusion
- The model performed well in complex tasks and multiple logical and reasoning questions.
- It demonstrated the ability to understand and correct issues related to Python version compatibility.
- The video suggests that viewers learn more about Nvidia Nim from a previous video linked in the content.
(Note: No detailed instructions such as CLI commands, website URLs, or tips were provided in the text for extraction.)