Image-to-Text
Transformers
PyTorch
English
qwen2vl
image-text-to-text
vision-language-model
quantized
chain-of-zoom
8-bit precision
super-resolution
qwen
multimodal
Eval Results (legacy)
Instructions to use humbleakh/qwen2.5-vl-3b-8bit-chain-of-zoom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use humbleakh/qwen2.5-vl-3b-8bit-chain-of-zoom with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="humbleakh/qwen2.5-vl-3b-8bit-chain-of-zoom")# Load model directly from transformers import AutoModelForImageTextToText model = AutoModelForImageTextToText.from_pretrained("humbleakh/qwen2.5-vl-3b-8bit-chain-of-zoom", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e02a6a2c7fa791dda550d041516c110850578ee5ceb510d63c30dcdba694c5c
- Size of remote file:
- 11.9 MB
- SHA256:
- 304ca4ccbade34ee33ab386441b88a9a215b1f5c626bdfd0305d8166623dceee
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