mirror of
https://github.com/hpcaitech/ColossalAI.git
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df5e9c53cf
* Add dpo. Fix sft, ppo, lora. Refactor all * fix and tested ppo * 2 nd round refactor * add ci tests * fix ci * fix ci * fix readme, style * fix readme style * fix style, fix benchmark * reproduce benchmark result, remove useless files * rename to ColossalChat * use new image * fix ci workflow * fix ci * use local model/tokenizer for ci tests * fix ci * fix ci * fix ci * fix ci timeout * fix rm progress bar. fix ci timeout * fix ci * fix ci typo * remove 3d plugin from ci temporary * test environment * cannot save optimizer * support chat template * fix readme * fix path * test ci locally * restore build_or_pr * fix ci data path * fix benchmark * fix ci, move ci tests to 3080, disable fast tokenizer * move ci to 85 * support flash attention 2 * add all-in-one data preparation script. Fix colossal-llama2-chat chat template * add hardware requirements * move ci test data * fix save_model, add unwrap * fix missing bos * fix missing bos; support grad accumulation with gemini * fix ci * fix ci * fix ci * fix llama2 chat template config * debug sft * debug sft * fix colossalai version requirement * fix ci * add sanity check to prevent NaN loss * fix requirements * add dummy data generation script * add dummy data generation script * add dummy data generation script * add dummy data generation script * update readme * update readme * update readme and ignore * fix logger bug * support parallel_output * modify data preparation logic * fix tokenization * update lr * fix inference * run pre-commit --------- Co-authored-by: Tong Li <tong.li352711588@gmail.com>
32 lines
934 B
Markdown
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32 lines
934 B
Markdown
Executable File
:warning: **This content may be outdated since the major update of Colossal Chat. We will update this content soon.**
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# ColossalAI on Ray
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## Abstract
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This is an experimental effort to run ColossalAI Chat training on Ray
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## How to use?
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### 1. Setup Ray clusters
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Please follow the official [Ray cluster setup instructions](https://docs.ray.io/en/latest/cluster/getting-started.html) to setup an cluster with GPU support. Record the cluster's api server endpoint, it should be something similar to http://your.head.node.addrees:8265
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### 2. Clone repo
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Clone this project:
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```shell
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git clone https://github.com/hpcaitech/ColossalAI.git
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```
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### 3. Submit the ray job
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```shell
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python applications/Chat/examples/community/ray/ray_job_script.py http://your.head.node.addrees:8265
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```
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### 4. View your job on the Ray Dashboard
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Open your ray cluster dashboard http://your.head.node.addrees:8265 to view your submitted training job.
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