Qwen GRPO Fine Tuning
Collection
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How to use vinhnx90/vt-qwen-3b-GRPO-merged-16bit-bnb-4bit with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("feature-extraction", model="vinhnx90/vt-qwen-3b-GRPO-merged-16bit-bnb-4bit") # Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("vinhnx90/vt-qwen-3b-GRPO-merged-16bit-bnb-4bit")
model = AutoModel.from_pretrained("vinhnx90/vt-qwen-3b-GRPO-merged-16bit-bnb-4bit", device_map="auto")This model is a quantized version of the original model vinhnx90/vt-qwen-3b-GRPO-merged-16bit.
It's quantized using the BitsAndBytes library to 4-bit using the bnb-my-repo space.
This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
Base model
vinhnx90/vt-qwen-3b-GRPO-merged-16bit