alanzhuly

Joined 4 years ago

Karma
147
Submissions
39
Member since
Feb 7
Advancing on-device AI.

Personal website: https://www.alanzhuly.com/

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Recent submissions

Comment · 1 year ago
Hi! I am from Nexa AI. We just improved Omnivision-968M based on your feedback! Here is a preview in our Hugging Face Space: https://huggingface.co/spaces/NexaAIDev/omnivlm-dpo-demo

The updated GGUF and safetensors will be released after final alignment tweaks. Please feel free to let us know if there's any other feedback!

Comment · 2 years ago
If we can have this running locally on mobile phone that would be pretty cool. Imagine receiving a work document (for example, product requirement documents), and then this turning it into a podcast to play for me while I am driving. I think my productivity will be through the roof and I don't need to worry about compliance issues.
Comment · 2 years ago
Hi Everyone!

We built an open-sourced tool to benchmark GGUF models with a single line of code. GitHub Link: https://github.com/NexaAI/nexa-sdk/tree/main/nexa/eval

Motivations:

GGUF quantization is crucial for running models locally on devices, but quantizations can dramatically affect model's performance. It's essential to test models post-quantization (how benchmark comes in clutch). But we noticed a couple of challenges:

1. No easy, fast way to benchmark quantized GGUF models locally or on self-hosted servers.

2. GGUF quantization evaluation results in the existing benchmarks are inconsistent, showing lower scores than the official results from model developers.

Our Solution - We built a tool that:

1. Benchmarks GGUF models with one line of code.

2. Supports multiprocessing and 8 evaluation tasks.

3. In our testing, it's the fastest benchmark for GGUF models available.

Example:

Type below in terminal to benchmark Llama3.2-1B-Instruct Q4_K_M quant on the "ifeval" dataset for general language understanding. It took 80 minutes on a 4090 with 4 workers for multiprocessing.

nexa eval Llama3.2-1B-Instruct:q4_K_M --tasks ifeval --num_workers 4

We started with text models and plan to expand to more on-device models and modalities. Your feedback is welcome! If you find this useful, feel free to let us know on GitHub: https://github.com/NexaAI/nexa-sdk/tree/main/nexa/eval

Comment · 2 years ago
Thanks for reporting. We are investigating this issue. Could you help submit an issue to our GitHub and provide a screenshot of the terminal (with pip show nexaai)? This could help us reproduce this issue faster. Much appreciated!

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