Instructions to use vamman/maplept2-reasoning-477fb32c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vamman/maplept2-reasoning-477fb32c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("empero-ai/Qwythos-9B-Claude-Mythos-5-1M") model = PeftModel.from_pretrained(base_model, "vamman/maplept2-reasoning-477fb32c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9c408023d7a1bd6af6f2688d446aa322ddfe40857a96880008d7f6093bcc0a6
- Size of remote file:
- 20 MB
- SHA256:
- 639e352c0f904c1875d448ebed6f6faac005fd3eb58393b7f1fb3ff044e5ca03
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.