Image-to-Text
Transformers
ONNX
Safetensors
vision-encoder-decoder
image-text-to-text
typst
math-ocr
formula-recognition
browser
grayscale
Instructions to use dbcccc/TypLens with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbcccc/TypLens 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="dbcccc/TypLens")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("dbcccc/TypLens") model = AutoModelForMultimodalLM.from_pretrained("dbcccc/TypLens", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,272 Bytes
f982163 | 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 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | {
"model_name": "TypLens V1.1",
"source_model_sha256": "d42cfd2da242a11ecdb1fe8727ee01e6896a116cd46f74357c4fdce90eebe788",
"server_fp32": {
"split": "reused IBEM development set",
"independent_test": false,
"reviewer": "AI assistant",
"independent_second_annotator": false,
"newly_reviewed_cases": 38,
"inherited_identical_image_and_prediction_cases": 97,
"decoding": {
"strategy": "greedy",
"max_new_tokens": 1023,
"forced_eos": false
},
"content_review": "Compare source symbols, indices, accents and structure; allow equivalent Typst syntax and nonessential spacing.",
"results": {
"step": 33544,
"total": 135,
"correct": 127,
"incorrect": 8,
"unresolved": 0,
"compile_success": 135,
"complete_generation": 135,
"exact_text_matches": 76,
"exact_reference_render_matches": 88,
"accepted_despite_text_difference": 51,
"accepted_despite_pixel_difference": 39,
"exact_text_but_content_failure": 0
}
},
"browser_smoke": {
"browser": "Microsoft Edge 153.0.4234.48",
"provider": "wasm",
"threads": 4,
"images_per_variant": 3,
"variants": [
"fp32",
"int8"
],
"completed_runs": 6,
"preprocessing_matches_training": true,
"tokens_match_cpu_onnx": true,
"tokens_match_server_fp32_on_these_images": true,
"known_content_error_present": "tilde accent recognized as hat on one smoke-test image",
"full_accuracy_evaluation": false
},
"export_versions": {
"torch": "2.8.0+cu128",
"transformers": "4.52.3",
"onnx": "1.18.0",
"onnxruntime": "1.22.0"
},
"controlled_v1_vs_v1_1_accuracy_comparison": false,
"quantized_full_accuracy_evaluation": false,
"source_record_sha256": {
"evaluation-full-generation-v1/completion-summary.json": "d889c42d2cb3f1333d84b77e7d86793d32660a491244be48eaf39eec50270b40",
"evaluation-full-generation-v1/source-review.json": "8b2a23a519889066591ab97c952493daaadf7fd4dcdee126be66d8e5215d4ab0",
"browser-final-v1/export-smoke.json": "63eb0c9acec09a71930bc8da1d300c7bcde0740cfa77f7cba12f104da2dcee77",
"browser-final-v1/browser-smoke.json": "c1904f5727209744b778604ec2d7aa65dcbeec3247f34bce3b36c179d285593a"
}
}
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