-
Notifications
You must be signed in to change notification settings - Fork 57
[doc] add tracking #504
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: main
Are you sure you want to change the base?
[doc] add tracking #504
Conversation
Summary of ChangesHello @slin1237, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request introduces a new documentation artifact to systematically track the testing status of a wide array of AI models, providing a centralized and detailed overview of their compatibility and performance. Concurrently, it updates the project's Go module dependencies, likely to support new features, improve stability, or maintain compatibility with evolving external services and libraries. Highlights
🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console. Using Gemini Code AssistThe full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips. Invoking Gemini You can request assistance from Gemini at any point by creating a comment using either
Customization To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a Limitations & Feedback Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here. You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension. Footnotes
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Code Review
This pull request introduces a comprehensive tracking document for model testing, which is a valuable addition for monitoring test coverage and status. The document is well-structured and detailed.
I've left a couple of comments on the new markdown file regarding minor data inconsistencies that should be addressed to ensure accuracy.
Additionally, this PR includes significant changes to the go.sum file, which seems unrelated to the documentation focus. It's best practice to separate dependency updates from documentation changes into their own pull requests. This helps maintain a clean and understandable commit history. Please consider moving the go.sum changes to a separate PR.
| # Model Test Tracking | ||
|
|
||
| **Last Updated**: 2025-12-05 | ||
| **Total Models**: 203 | **Total Runtimes**: 187 |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
There's an inconsistency in the total number of runtimes reported. The header states Total Runtimes: 187, but the Runtime Coverage section on line 244 indicates that 163 models have a runtime. Based on the master list, 163 seems to be the correct number (203 total models - 40 models without a runtime). Please update the total in the header for consistency.
| ## Failure Categories | ||
|
|
||
| | Category | Count | Examples | | ||
| |----------------------------|-------|--------------------------------------------------------| | ||
| | Architecture not supported | 12 | Bloom, Falcon, GPT-J, GPT-NeoX, StableLM, CodeGen, MPT | | ||
| | Download timeout | 8 | Large models, gated models, system issues | | ||
| | CUDA OOM | 3 | DeepSeek-V3, Llama-4-Maverick (non-FP8) | | ||
| | Module missing | 3 | phi-2, phi-3-mini (vllm module) | | ||
| | HuggingFace access | 2 | Gated models requiring license | | ||
| | Inference issues | 2 | FP8 NaN, warmup failures | | ||
| | Other | 10 | Various configuration/compatibility issues | |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
There appear to be some inconsistencies in the failure analysis:
- Contradiction for MPT: The
Failure Categoriestable listsMPTas an example of an unsupported architecture. However, theSupported Text Generation Architecturestable on line 294 includesMptForCausalLM, and thempt-7bmodel in the master list failed due to a "Download timeout", not an architecture issue. - Incorrect Count: This table states there are 12 models with an unsupported architecture. However, I could only identify 7 models in the master list that failed for this reason.
Could you please verify these details and update the tables for accuracy?
|
@slin1237 : Could you break down the the SUPPORTED MODEL markdown for model families (or vendor) for each of the modalities (text, multimodal, embed, rerank, reward). Thanks! Also add corresponding recommended hardware shapes. Remove large models that aren't supported (like Deepseek v3) |
What this PR does
Why we need it
Fixes #
How to test
Checklist
make testpasses locally