Downloads · 30 days
24
46% of all-time downloads
Litian2002/Qwen2.5-VL-3B-Spatial-bnb-4bit
Qwen2.5-VL-3B-Spatial-bnb-4bit is a machine learning model from Litian2002. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This repository contains the merged weights of LoRA adapter located at ./finalmodel and the base model unsloth/Qwen2.5-VL-3B-Instruct-bnb-4bit.
Downloads · 30 days
24
46% of all-time downloads
All-time downloads
52
Public
Parameters
3.9B
2.5 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors2.5 GB · 99%
How the weights are stored.
U83.5B · 91%
From the Hugging Face model README
This repository contains the merged weights of LoRA adapter located at ./final_model and the base
model unsloth/Qwen2.5-VL-3B-Instruct-bnb-4bit.
The merge was performed with peft.merge_and_unload() on 2025-06-04.
from unsloth import FastVisionModel
model, tokenizer = FastVisionModel.from_pretrained("Litian2002/Qwen2.5-VL-3B-Spatial-bnb-4bit")
model = FastVisionModel.for_inference(model) # Enable native 2x faster inference
# Your inference code here
Or with transformers:
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("Litian2002/Qwen2.5-VL-3B-Spatial-bnb-4bit", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("Litian2002/Qwen2.5-VL-3B-Spatial-bnb-4bit", trust_remote_code=True)