Instructions to use microsoft/trocr-small-printed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/trocr-small-printed 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="microsoft/trocr-small-printed")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/trocr-small-printed") model = AutoModelForMultimodalLM.from_pretrained("microsoft/trocr-small-printed") - Notebooks
- Google Colab
- Kaggle
ValueError: Unrecognized feature extractor in microsoft/trocr-base-handwritten. Should have a `feature_extractor_type` key in its preprocessor_config.json of config.json, or one of the following `model_type` keys in its {CONFIG_NAME}: {', '.join(c for c in FEATURE_EXTRACTOR_MAPPING_NAMES.keys())}
#7
by ram1813 - opened
No description provided.
f"Unrecognized feature extractor in {pretrained_model_name_or_path}. Should have a "
ValueError: Unrecognized feature extractor in microsoft/trocr-large-handwritten. Should have a feature_extractor_type key in its preprocessor_config.json of config.json, or one of the following model_type keys in its {CONFIG_NAME}: {', '.join(c for c in FEATURE_EXTRACTOR_MAPPING_NAMES.keys())}
I am still getting this error.