Instructions to use ruhai-lin/MixerLoop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruhai-lin/MixerLoop with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ruhai-lin/MixerLoop", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download legacy/fullloop-15m/eval/core_eval.csv from ruhai-lin/MixerLoop: direct link, hf CLI and curl.
- Browser
- Download file 777 Bytes
-
https://huggingface.co/ruhai-lin/MixerLoop/resolve/main/legacy/fullloop-15m/eval/core_eval.csv
- Command line
-
hf download hf://ruhai-lin/MixerLoop/legacy/fullloop-15m/eval/core_eval.csv
-
curl -L -o core_eval.csv https://huggingface.co/ruhai-lin/MixerLoop/resolve/main/legacy/fullloop-15m/eval/core_eval.csv
777 Bytes
| Task,Accuracy,Centered | |
| hellaswag_zeroshot,0.284605,0.046140 | |
| jeopardy,0.000472,0.000472 | |
| bigbench_qa_wikidata,0.063826,0.063826 | |
| arc_easy,0.393098,0.190797 | |
| arc_challenge,0.230375,-0.026166 | |
| copa,0.460000,-0.080000 | |
| commonsense_qa,0.199017,-0.001229 | |
| piqa,0.603917,0.207835 | |
| openbook_qa,0.286000,0.048000 | |
| lambada_openai,0.146711,0.146711 | |
| hellaswag,0.281418,0.041891 | |
| winograd,0.534799,0.069597 | |
| winogrande,0.482242,-0.035517 | |
| bigbench_dyck_languages,0.007000,0.007000 | |
| agi_eval_lsat_ar,0.234783,0.043478 | |
| bigbench_cs_algorithms,0.384848,0.384848 | |
| bigbench_operators,0.090476,0.090476 | |
| bigbench_repeat_copy_logic,0.000000,0.000000 | |
| squad,0.016840,0.016840 | |
| coqa,0.055618,0.055618 | |
| boolq,0.528746,-0.240142 | |
| bigbench_language_identification,0.258100,0.183828 | |
| CORE,,0.055196 | |