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-110m/eval/core_eval.csv from ruhai-lin/MixerLoop: direct link, hf CLI and curl.
- Browser
- Download file 773 Bytes
-
https://huggingface.co/ruhai-lin/MixerLoop/resolve/main/legacy/fullloop-110m/eval/core_eval.csv
- Command line
-
hf download hf://ruhai-lin/MixerLoop/legacy/fullloop-110m/eval/core_eval.csv
-
curl -L -o core_eval.csv https://huggingface.co/ruhai-lin/MixerLoop/resolve/main/legacy/fullloop-110m/eval/core_eval.csv
773 Bytes
| Task,Accuracy,Centered | |
| hellaswag_zeroshot,0.433579,0.244772 | |
| jeopardy,0.027870,0.027870 | |
| bigbench_qa_wikidata,0.381477,0.381477 | |
| arc_easy,0.587963,0.450617 | |
| arc_challenge,0.308020,0.077361 | |
| copa,0.560000,0.120000 | |
| commonsense_qa,0.313677,0.142097 | |
| piqa,0.691513,0.383025 | |
| openbook_qa,0.360000,0.146667 | |
| lambada_openai,0.323501,0.323501 | |
| hellaswag,0.432185,0.242913 | |
| winograd,0.593407,0.186813 | |
| winogrande,0.522494,0.044988 | |
| bigbench_dyck_languages,0.199000,0.199000 | |
| agi_eval_lsat_ar,0.256522,0.070652 | |
| bigbench_cs_algorithms,0.431818,0.431818 | |
| bigbench_operators,0.152381,0.152381 | |
| bigbench_repeat_copy_logic,0.031250,0.031250 | |
| squad,0.097919,0.097919 | |
| coqa,0.141927,0.141927 | |
| boolq,0.537920,-0.215999 | |
| bigbench_language_identification,0.249200,0.174037 | |
| CORE,,0.175231 | |