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[Github] Add issue templates. (octoml#265)
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yzh119 authored May 29, 2023
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43 changes: 43 additions & 0 deletions .github/ISSUE_TEMPLATE/bug-report.md
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---
name: "🐛 Bug Report"
about: Submit a bug report to help us improve MLC-LLM
title: ''
labels: ''
assignees: ''

---

## 🐛 Bug

<!-- A clear and concise description of what the bug is. -->

## To Reproduce

Steps to reproduce the behavior:

1.
1.
1.

<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->

## Expected behavior

<!-- A clear and concise description of what you expected to happen. -->

## Environment

- Platform (e.g. WebGPU/Vulkan/IOS/Android/CUDA):
- Operating system (e.g. Ubuntu/Windows/MacOS/...):
- Device (e.g. iPhone 12 Pro, PC+RTX 3090, ...)
- How you installed MLC-LLM (`conda`, source):
- How you installed TVM-Unity (`pip`, source):
- Python version (e.g. 3.10):
- GPU driver version (if applicable):
- CUDA/cuDNN version (if applicable):
- TVM Unity Hash Tag (`python -c "import tvm; print('\n'.join(f'{k}: {v}' for k, v in tvm.support.libinfo().items()))"`, applicable if you compile models):
- Any other relevant information:

## Additional context

<!-- Add any other context about the problem here. -->
7 changes: 7 additions & 0 deletions .github/ISSUE_TEMPLATE/config.yml
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blank_issues_enabled: false

contact_links:
- name: Check the MLC-LLM Documentation
url: https://mlc.ai/mlc-llm/docs/
- name: Chat on Discord
url: https://discord.gg/9Xpy2HGBuD
17 changes: 17 additions & 0 deletions .github/ISSUE_TEMPLATE/documentation.md
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---
name: "\U0001F4DA Documentation"
about: Report an issue related to https://mlc.ai/mlc-llm/docs
title: ''
labels: ''
assignees: ''

---

## 📚 Documentation

### Suggestion
<!-- Please leave your general suggestion to our documentation here. -->

### Bug
- Link to the buggy documentation/tutorial:
- Description of the bug:
23 changes: 23 additions & 0 deletions .github/ISSUE_TEMPLATE/feature-request.md
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---
name: "\U0001F680 Feature Request"
about: Submit a proposal/request for a new MLC-LLM feature, or an enhancement on existing features.
title: ''
labels: ''
assignees: ''

---

## 🚀 Feature
<!-- A brief description of the feature proposal -->

## Motivation

<!-- Please outline the motivation for the proposal, and how could this feature benefit the MLC-LLM project/community. -->

## Alternatives

<!-- A clear and concise description of any alternative solutions or features you've considered, if any. -->

## Additional context

<!-- Add any other context or screenshots about the feature request here. -->
13 changes: 13 additions & 0 deletions .github/ISSUE_TEMPLATE/general.md
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---
name: "❓ General Questions"
about: .
title: ''
labels: ''
assignees: ''

---

## ❓ General Questions

<!-- Describe your questions -->

17 changes: 17 additions & 0 deletions .github/ISSUE_TEMPLATE/model-request.md
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---
name: "️️⚙️ Model Request"
about: Request a new model in MLC-LLM
title: ''
labels: ''
assignees: ''

---

## ⚙️ Request New Models

- Link to an existing implementation (e.g. Hugging Face/Github): <!-- Link to the model -->
- Is this model architecture supported by MLC-LLM? (the list of [supported models](https://mlc.ai/mlc-llm/docs/model-zoo.html#id7)) <!-- Yes/No -->

## Additional context

<!-- Add any other context that you think would be helpful for the community to add this model -->
24 changes: 24 additions & 0 deletions .github/ISSUE_TEMPLATE/speed-report.md
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---
name: " 🏎️ Speed Report"
about: Submit a speed report of an model running in MLC-LLM
title: ''
labels: ''
assignees: ''

---

# 🏎️ Speed Report

<!-- Please search if there are existing issues discuss the speed of the model you are using, if there are, we encourage you reply in the existed issue instead of creating a new one. -->

- The model code: <!-- e.g. vicuna-7b-1.1 -->


- The model configuration (e.g. quantization mode, running data type, etc.):
- Device (e.g. MacBook Pro M2, PC+RTX 3080):
- OS (if applicable):
- Encode speed (Token/s):
- Decode speed (Token/s):
- Memory usage (if applicable):

<!-- Note that the measured speed might reflect peak performance if the prompt/chat history is short. -->

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