Instructions to use openthaigpt/thai-trocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openthaigpt/thai-trocr 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="openthaigpt/thai-trocr")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("openthaigpt/thai-trocr") model = AutoModelForMultimodalLM.from_pretrained("openthaigpt/thai-trocr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -64,7 +64,7 @@ This section details the performance comparison between the open-source ThaiTrOC
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| Scene Text | **0.134182** | 0.390583 | 2.408704 |
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| **Adjusted Mean** | **0.123600** | 0.298474 | 1.269101 |
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**Disclaimer**: The test dataset at https://huggingface.co/datasets/openthaigpt/thai-ocr-evaluation includes only
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# Key Insights
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| Scene Text | **0.134182** | 0.390583 | 2.408704 |
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| **Adjusted Mean** | **0.123600** | 0.298474 | 1.269101 |
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**Disclaimer**: The test dataset at https://huggingface.co/datasets/openthaigpt/thai-ocr-evaluation includes only 104 images, which may limit the generalizability of these results. We are increasing the number of the test dataset.
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# Key Insights
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