Text Generation
PEFT
Safetensors
lora
grpo
swe-bench
code
banya
rlvr
dense-reward
ablation
conversational
Instructions to use banyaaiofficial/Qwen3.5-122B-A10B-Banya-Tuned-v20-grpo-ckpt80 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use banyaaiofficial/Qwen3.5-122B-A10B-Banya-Tuned-v20-grpo-ckpt80 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-122B-A10B") model = PeftModel.from_pretrained(base_model, "banyaaiofficial/Qwen3.5-122B-A10B-Banya-Tuned-v20-grpo-ckpt80") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37bf8e91c59bf299774e47a1f4a9895d5be4d99f3ad5eda248748bca8f94d860
- Size of remote file:
- 14.6 MB
- SHA256:
- 5da84e75b7076a44785d71fcfec75daf8f5b9afd5b03d63d46c39cf72e2bbec8
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