Image-to-Text
Transformers
RKLLM
ONNX
OCR
vision-language
VLM
Reasoning
document-to-markdown
qwen2.5
markdown
extraction
RAG
Instructions to use Prince-1/NuMarkdown-8B-Thinking-Rkllm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prince-1/NuMarkdown-8B-Thinking-Rkllm 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="Prince-1/NuMarkdown-8B-Thinking-Rkllm")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Prince-1/NuMarkdown-8B-Thinking-Rkllm", dtype="auto") - RKLLM
How to use Prince-1/NuMarkdown-8B-Thinking-Rkllm with RKLLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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