Reinforcement Learning
Transformers
Safetensors
English
qwen3
text-generation
grpo
trl
structured-output
sft-to-grpo
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use zerg2187/GRPO_structeval_t_qwen3_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zerg2187/GRPO_structeval_t_qwen3_v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zerg2187/GRPO_structeval_t_qwen3_v1") model = AutoModelForCausalLM.from_pretrained("zerg2187/GRPO_structeval_t_qwen3_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dd79aa1fb4c208adad76c1910b7104edaa2679562bc0067af5aea044b373410
- Size of remote file:
- 11.4 MB
- SHA256:
- 67cc0080ffd7555f723f423c27cfef314e1ad9d335c8b79f465c5faba1ed478b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.