Instructions to use aymanbakiri/MNLP_M3_mcqa_sft_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aymanbakiri/MNLP_M3_mcqa_sft_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("AnnaelleMyriam/MNLP_M3_sft_dpo_1024_beta0.5_2e-5_FINAL_v3_16_check1500") model = PeftModel.from_pretrained(base_model, "aymanbakiri/MNLP_M3_mcqa_sft_model") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
- Xet hash:
- a42ec1dff2acc0b0e33d599662b5532403236a7d2f45da221b0ddfd38921838f
- Size of remote file:
- 5.78 kB
- SHA256:
- 0573318ea7582641fe31ca2dfe8b4b6aff5ecdf9c8683110e93c42da9f88efb6
路
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