Text Generation
PEFT
Safetensors
English
lora
trl
nyt-connections
puzzle-solving
grpo
reinforcement-learning
rlvr
reward-over-optimization
negative-results
conversational
Eval Results (legacy)
Instructions to use jacksonlukas/connections-rl-grpo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jacksonlukas/connections-rl-grpo with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "jacksonlukas/connections-rl-grpo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e04126006d1b777c800985639d532efc3da2206e76c75e4e6f74c368677856d
- Size of remote file:
- 7.57 kB
- SHA256:
- 1f7ec1cbdef36a8fce825ce489c475b764c43ceb60971ae0453909d00525c893
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.