Image-to-Text
Transformers
Safetensors
deepseek_vl_v2
feature-extraction
vision
ocr
quantized
qvlm
4-bit precision
deepseek
custom_code
8-bit precision
Instructions to use SamMikaelson/deepseek-ocr-qvlm-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamMikaelson/deepseek-ocr-qvlm-4bit 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="SamMikaelson/deepseek-ocr-qvlm-4bit", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SamMikaelson/deepseek-ocr-qvlm-4bit", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 460 Bytes
b0c459a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"add_special_token": false,
"candidate_resolutions": [
[
1024,
1024
]
],
"downsample_ratio": 4,
"ignore_id": -100,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"image_token": "<image>",
"mask_prompt": false,
"normalize": true,
"pad_token": "<\uff5c\u2581pad\u2581\uff5c>",
"patch_size": 16,
"processor_class": "DeepseekVLV2Processor",
"sft_format": "deepseek"
}
|