Enable mixtral 8x7b accuracy evaluation#1986
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regisss merged 7 commits intoJun 3, 2025
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vidyasiv
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Contacted author offline, they're busy now and will respond in 1-2 weeks. |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
astachowiczhabana
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Thanks for really good review :) |
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@regisss can we merge this to main/1.18. The code is separated and shouldn't disrupt current tests results |
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Co-authored-by: Rafal <rbogdanowicz@habana.ai>
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* Merge v1.18-release * Hot fix regional compilation (huggingface#2005) Co-authored-by: regisss <15324346+regisss@users.noreply.github.com> * Enable mixtral 8x7b accuracy evaluation (huggingface#1986) Co-authored-by: Rafal <rbogdanowicz@habana.ai> * Update readme files for explicit lazy mode (huggingface#1921) Co-authored-by: Karol Brejna <karol.brejna@intel.com> Co-authored-by: Piotr Bielak <piotr.bielak@intel.com> * [llama-vision] Remove token_idx_cpu parameter (huggingface#2018) Integer parameter token_idx_cpu passed to mllama's forward() method caused an issue with hpu graph cache which led to performance drop. Signed-off-by: Urszula <urszula.golowicz@intel.com> * Update README examples (huggingface#2020) * Fix examples in README audio-classification: - add space between "False" and backslash image-to-text: - add "datasets" to requirements.txt pytorch-image-models: - add "datasets" to requirements.txt sentence-transformers-training/nli: - add command to properly discover HABANA_VISIBLE_MODULES sentence-transformers-training/sts: - add command to properly discover HABANA_VISIBLE_MODULES speech-recognition: - add `--trust_remote_code` for seq2seq examples stable-diffusion/training: - add missing OpenCV requirement for ControlNet Training Co-authored-by: Karol Brejna <karol.brejna@intel.com> * Review fixes: remove grabbing all modules --------- Co-authored-by: Karol Brejna <karol.brejna@intel.com> Co-authored-by: karol-brejna-i <karolbrejna@apache.org> * Pin latest optimum to force mutual updates (huggingface#2016) pin latest optimum to force mutual updates * Fix FP8 support and address related issues (huggingface#2010) - Resolve bugs related to FP8 (floating point 8-bit) computation - Improve stability and correctness of FP8 operations - Add/fix tests to validate FP8 functionality - Update relevant documentation and comments Co-authored-by: IlyasMoutawwakil --------- Signed-off-by: Urszula <urszula.golowicz@intel.com> Co-authored-by: Adam Stachowicz <astachowicz@habana.ai> Co-authored-by: Ilyas Moutawwakil <57442720+IlyasMoutawwakil@users.noreply.github.com> Co-authored-by: regisss <15324346+regisss@users.noreply.github.com> Co-authored-by: Rafal Bogdanowicz <rafal.bogdanowicz@intel.com> Co-authored-by: Rafal <rbogdanowicz@habana.ai> Co-authored-by: Jan Kamiński <jkaminski@habana.ai> Co-authored-by: Karol Brejna <karol.brejna@intel.com> Co-authored-by: Piotr Bielak <piotr.bielak@intel.com> Co-authored-by: Urszula Golowicz <urszula.golowicz@intel.com> Co-authored-by: Piotr Bielak <pbielak@users.noreply.github.com> Co-authored-by: karol-brejna-i <karolbrejna@apache.org>
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This commit implements accuracy.json generation.
In order to generate inference responses for custom dataset simply run run_generation script with two parameters --dataset custom_dataset.pkl and --dataset_name custom.
Additionaly you can setup environment for mbxp dataset evaluation and evaluate responses by using mlcommon scripts.
Results from the evaluation of the mlcommon dataset, which is a combination of OpenOrca, GSM8K, and MBXP.
{
'rouge1': 45.4708,
'rouge2': 23.2887,
'rougeL': 30.3478,
'rougeLsum': 42.4501,
'gsm8k': 74.16,
'mbxp': 60.36,
'gen_len': 4243067,
'gen_num': 15000,
'gen_tok_len': 2808861,
'tokens_per_sample': 187.3
}