Instructions to use TYTTYTTYT/zf_qwen3_vl_processor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TYTTYTTYT/zf_qwen3_vl_processor with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TYTTYTTYT/zf_qwen3_vl_processor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
adapt to transformers==4.57.6
Browse files
image_processing_qwen2_vl_fast.py
CHANGED
|
@@ -43,6 +43,8 @@ class Qwen2VLFastImageProcessorKwargs(DefaultFastImageProcessorKwargs):
|
|
| 43 |
The temporal patch size of the vision encoder.
|
| 44 |
merge_size (`int`, *optional*, defaults to 2):
|
| 45 |
The merge size of the vision encoder to llm encoder.
|
|
|
|
|
|
|
| 46 |
"""
|
| 47 |
|
| 48 |
min_pixels: Optional[int]
|
|
|
|
| 43 |
The temporal patch size of the vision encoder.
|
| 44 |
merge_size (`int`, *optional*, defaults to 2):
|
| 45 |
The merge size of the vision encoder to llm encoder.
|
| 46 |
+
focus_size (`int`, *optional*, defaults to 2):
|
| 47 |
+
The focus size of the ZoomFocus.
|
| 48 |
"""
|
| 49 |
|
| 50 |
min_pixels: Optional[int]
|