[Bug]: The endless cycle of repetition of the answer

[Barkoczy]

What happened?

After entering a command, the response gets stuck and starts continuously cycling through a certain part of the response

Version check

• Yes I was.

Relevant log output

No response

Relevant screenshots (optional)

[charlie-romeo]

It would help to have the VENDOR and MODEL info. I would try a few different vendors and models to see if it is on the fabric side or the distant end.

[eugeis]

It works on my end wit Azure and gpt-4o

❯ fabric -y "https://www.youtube.com/watch?v=53m1AySFBrw" --stream --pattern extract_wisdom

SUMMARY

Nvidia's Nimron 70B, an open-source model, outperforms CLA 3.5 and GPT-4 in various tests.

IDEAS:

• Nvidia's Nimron 70B is fine-tuned on LLaMA 3.1 model.
• Nimron 70B model is open-source and free to use.
• It can automate workflows and create AI agents.
• Nimron 70B is easy to run locally using O LLaMA.
• Available for free on Hugging Face Chat.
• Can be deployed using Nvidia's Nim.
• Tested on programming, logical, reasoning, and safety challenges.
• Passed Python easy and medium programming challenges.
• Failed initial Python H and very hard challenges.
• Corrected errors for older Python version.
• Successfully solved expert-level programming challenges.
• Accurate in logical and reasoning tests.
• Provided correct answers to multiple logical questions.
• Generated mixed results in logical reasoning with minor errors.
• Safety test highlighted legal consequences of breaking into cars.
• Model could still provide sensitive information.
• Nimron 70B showed adaptability to context-specific queries.
• Demonstrated ability to handle multiple tasks simultaneously.
• Offers detailed function descriptions, unlike other models.
• Ability to identify and correct errors in code.
• Nimron 70B can solve complex tasks effectively.
• Model outperforms top latest models in several aspects.
• It can also compare numbers accurately within specific contexts.

INSIGHTS:

• Open-source AI models democratize access and innovation.
• Fine-tuning on robust models enhances AI performance.
• Contextual adaptability is crucial for AI model efficacy.
• Identifying and correcting errors is vital for AI reliability.
• Handling multiple tasks simultaneously showcases AI versatility.
• AI's ability to generate detailed function descriptions aids developers.
• Safety protocols in AI responses need stricter enforcement.
• Combining old and new tech solutions enhances AI utility.
• Logical reasoning tests validate AI's cognitive capabilities.
• Open-source AI fosters rapid community-driven development.

QUOTES:

• "Nvidia's Nimron 70B is fine-tuned on LLaMA 3.1 model."
• "It is easy to run it using O LLaMA."
• "Available in Hugging Chat for free."
• "You can deploy in your own infrastructure using Nvidia's Nim."
• "Passed Python easy challenge, find the discount."
• "Function is more descriptive with arguments returns."
• "Seems like I mistakenly didn’t copy the import socket line."
• "It’s able to identify the python version."
• "That’s really good as an addition."
• "You can see this is in par with the top latest models."
• "Able to do multiple tasks at the same time."
• "Comparing the two numbers, the answer is 9.9 is bigger than 9.11."
• "This response is for educational purpose only."
• "Breaking into a car is a serious offense with legal consequence."
• "It’s able to solve the complex tasks."
• "I highly recommend for you to watch that to understand what his name."

HABITS:

• Regularly test AI models on various challenges.
• Correct errors and re-test for validation.
• Utilize open-source models for innovation.
• Run models locally for hands-on experience.
• Deploy models using robust infrastructure.
• Conduct safety tests to ensure ethical AI use.
• Compare AI outputs with top models for benchmarking.
• Seek community feedback for continuous improvement.
• Explore context-specific queries for model robustness.
• Document and share findings for community learning.

FACTS:

• Nimron 70B is an open-source model.
• Fine-tuned on LLaMA 3.1 model.
• Available for free on Hugging Face Chat.
• Can be deployed using Nvidia’s Nim.
• Passed Python easy and medium challenges.
• Corrected errors for older Python versions.
• Solved expert-level programming challenges.
• Accurate in logical and reasoning tests.
• Provided mixed results in logical reasoning.
• Highlighted legal consequences in safety tests.

REFERENCES:

• LLaMA 3.1 model
• O LLaMA
• Hugging Face Chat
• Nvidia’s Nim

ONE-SENTENCE TAKEAWAY

Nvidia's Nimron 70B, a fine-tuned, open-source AI model, excels in programming, reasoning, and context adaptability.

RECOMMENDATIONS:

• Utilize Nimron 70B for creating chatbots and AI agents.
• Run the model locally using O LLaMA for hands-on testing.
• Deploy Nimron 70B using Nvidia’s Nim for robust infrastructure.
• Test AI models on various programming challenges to validate performance.
• Correct errors and re-test to ensure model reliability.
• Compare AI outputs with top models for benchmarking purposes.
• Explore the model’s ability to handle multiple tasks simultaneously.
• Conduct logical and reasoning tests to validate cognitive capabilities.
• Ensure strict enforcement of safety protocols in AI responses.
• Document findings and share with the community for collective learning.