sgl-project / sgl-project/SpecForge

[Bug] prepare_data.py: error: unrecognized arguments: --output_path /home/luor/.cache/huggingface/xxxx/dataset/ --test-size 0.01

Open
#229 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
1.2k
Forks
347
Avg merge
4d 1h
Merged PRs (30d)
41

Description

Checklist
  • 1. I have searched related issues but cannot get the expected help.
  • 2. The bug has not been fixed in the latest version.
  • 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback.
  • 4. If the issue you raised is not a bug but a question, please raise a discussion at https://github.com/sgl-project/SpecForge/discussions/new/choose Otherwise, it will be closed.
  • 5. Please use English, otherwise it will be closed.
Describe the bug

when i try
bash examples/run_llama3_eagle3_offline.sh,
i encountered the above issue.

Reproduction

bash examples/run_llama3_eagle3_offline.sh

Environment

accelerate 1.6.0
datasets 4.0.0
python 3.10.18
torch 2.8.0
transformers 4.55.2
triton 3.4.0
sglang 0.5.1

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by running bash examples/run_llama3_eagle3_offline.sh and inspect the prepare_data.py argument parser for the reported --output_path and --test-size options. Confirm the command completes without the unrecognized-arguments error and that data preparation reaches its next step.

Written by the indexing model from the issue text.

Assessment

Tech stack
bash, python
Domain
cli, machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
40/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.