Visual Question Answering
Transformers
Safetensors
English
Chinese
qwen2
text-generation
multimodal
text-generation-inference
Instructions to use BAAI/Aquila-VL-2B-llava-qwen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/Aquila-VL-2B-llava-qwen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="BAAI/Aquila-VL-2B-llava-qwen")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BAAI/Aquila-VL-2B-llava-qwen") model = AutoModelForCausalLM.from_pretrained("BAAI/Aquila-VL-2B-llava-qwen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Clarification on BAAI/Aquila-VL-2B-llava-qwen training origin
#5
by dqdw - opened
Dear [Developer/Team],
Thanks for releasing BAAI/Aquila-VL-2B-llava-qwen. I've been experimenting with it and it works well.
As I am planning to build upon this model, I would like to clarify its relationship with Qwen/Qwen2.5-1.5B-Instruct based on the model tree on Hugging Face:
Direct Fine-tuning: Is BAAI/Aquila-VL-2B-llava-qwen a direct fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct, or were there intermediate models/checkpoints involved?
Inheritance: Does it keep the same architecture and weights as Qwen/Qwen2.5-1.5B-Instruct?
This clarification would help me avoid compatibility issues.
Thank you for your time and support!