abacaj / code-eval Goto Github PK
View Code? Open in Web Editor NEWRun evaluation on LLMs using human-eval benchmark
License: MIT License
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annejeevan pengking apollohuang1 kustomzone tomchapin tmm1 techthiyanes torusresearch mayi140611 yuping322 vital121 yuexihang abdoiiii 44670 zhouwenyang epinnock prozek acrastt xuefuzhao wangdq1989 jinlkj baobaogithub xxw11 infinitylogesh s1530129650 evelynmitchell stophobia learner-crapy lvnwpu changpeng08 yangzhou08 xiechengmude plseal mathisallcode-eval's Issues
No GPU Found
@abacaj My environment is NVIDIA TX2， when use the package codecarbon to get information of GPU，but it can not find GPU:
[codecarbon INFO @ 21:03:55] [setup] RAM Tracking...
[codecarbon INFO @ 21:03:55] [setup] GPU Tracking...
[codecarbon INFO @ 21:03:55] No GPU found.
[codecarbon INFO @ 21:03:55] [setup] CPU Tracking...
[codecarbon WARNING @ 21:03:55] No CPU tracking mode found. Falling back on CPU constant mode.
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
[codecarbon WARNING @ 21:03:55] We saw that you have a ARMv8 Processor rev 1 (v8l) but we don't know it. Please contact us.
[codecarbon INFO @ 21:03:55] CPU Model on constant consumption mode: ARMv8 Processor rev 1 (v8l)
[codecarbon INFO @ 21:03:55] >>> Tracker's metadata:
[codecarbon INFO @ 21:03:55] Platform system: Linux-5.10.104-tegra-aarch64-with-glibc2.17
[codecarbon INFO @ 21:03:55] Python version: 3.8.13
[codecarbon INFO @ 21:03:55] CodeCarbon version: 2.3.4
[codecarbon INFO @ 21:03:55] Available RAM : 6.329 GB
[codecarbon INFO @ 21:03:55] CPU count: 6
[codecarbon INFO @ 21:03:55] CPU model: ARMv8 Processor rev 1 (v8l)
[codecarbon INFO @ 21:03:55] GPU count: None
[codecarbon INFO @ 21:03:55] GPU model: None
But the result of torch.cuda.is_available() is true， so i want to know if ``` codecarbon`` could suport the facility TX2? Looking forward to your reply.
Performance of llama-2
Why am I getting low scores on llama-2-13b, pass@1: 3.05%, pass@10: 19.51%, are you applying any other fine prompts to this setup or are the scores related to batch decoding, my setup is such that I need to generate the samples sequentially and can't perform batch decoding.
Any update on these metrics?
where can i get the result of perfrmance after evaluating the llama2-7b
@abacaj after evaluating the llama2-7b. i only get a file eval.json:
so how can i get the result following:
Any plans on running evals for codellama?
I'm keeping https://github.com/ErikBjare/are-copilots-local-yet up-to-date, and would love to see some codellama numbers given it's now SOTA :)
Support CodeGeeX2
建议支持 https://github.com/THUDM/CodeGeeX2 刚刚发布，根据公布1@pass数据达到了35.9
Is llama2-7B-chat weaker thank llama2-7B?
I got only 9.7% for llama2-7B-chat on human-eval using your script
{'pass@1': 0.0975609756097561}where the evaluate_functional_correctness
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