Instructions to use 10ths/FADS_base_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 10ths/FADS_base_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="10ths/FADS_base_model", trust_remote_code=True)# Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("10ths/FADS_base_model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- preprocessor_config.json +23 -0
preprocessor_config.json
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{
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"auto_map": {
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"AutoImageProcessor": "Salesforce/xgen-mm-phi3-mini-instruct-r-v1--image_processing_blip_3.Blip3ImageProcessor"
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},
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"do_resize": true,
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_processor_type": "Blip3ImageProcessor",
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"interpolation_mode": "bicubic",
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"resize_mode": "squash",
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"size": [
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378,
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]
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}
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