Update preprocessor_config.json
#24
by
Isotr0py
- opened
transformers
has used Qwen2VLImageProcessor
as Qwen2.5-VL's image processor. We need to update accordingly (see https://github.com/huggingface/transformers/pull/36164#issuecomment-2658902781)
Hi @Isotr0py ,
You have broken it! I'm getting this error trying to use it
Unrecognized image processor in Qwen/Qwen2.5-VL-7B-Instruct. Should have a `image_processor_type` key in its preprocessor_config.json of config.json, or one of the following `model_type` keys in its config.json: align, aria, beit, bit, blip, blip-2, bridgetower, chameleon, chinese_clip, clip, clipseg, conditional_detr, convnext, convnextv2, cvt, data2vec-vision, deformable_detr, deit, depth_anything, depth_pro, deta, detr, dinat, dinov2, donut-swin, dpt, efficientformer, efficientnet, flava, focalnet, fuyu, git, glpn, got_ocr2, grounding-dino, groupvit, hiera, idefics, idefics2, idefics3, ijepa, imagegpt, instructblip, instructblipvideo, kosmos-2, layoutlmv2, layoutlmv3, levit, llava, llava_next, llava_next_video, llava_onevision, mask2former, maskformer, mgp-str, mllama, mobilenet_v1, mobilenet_v2, mobilevit, mobilevitv2, nat, nougat, oneformer, owlv2, owlvit, paligemma, perceiver, pix2struct, pixtral, poolformer, pvt, pvt_v2, qwen2_5_vl, qwen2_vl, regnet, resnet, rt_detr, sam, segformer, seggpt, siglip, superglue, swiftformer, swin, swin2sr, swinv2, table-transformer, timesformer, timm_wrapper, tvlt, tvp, udop, upernet, van, videomae, vilt, vipllava, vit, vit_hybrid, vit_mae, vit_msn, vitmatte, xclip, yolos, zoedepth.
manually removing new line in preprocessor_config.json
fixes the issue. Please find another option.
@alxgrh
You might need to add revision="refs/pr/24"
currently when initializing the processor, because this PR hasn't been merged yet.
from transformers import AutoProcessor
processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct", revision="refs/pr/24")
print(processor)
Outputs:
Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_processor_type": "Qwen2VLImageProcessor",
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"max_pixels": 12845056,
"merge_size": 2,
"min_pixels": 3136,
"patch_size": 14,
"processor_class": "Qwen2_5_VLProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"longest_edge": 12845056,
"shortest_edge": 3136
},
"temporal_patch_size": 2
}