Instructions to use tosin/LLaDoc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tosin/LLaDoc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tosin/LLaDoc")# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("tosin/LLaDoc") model = AutoModelForCausalLM.from_pretrained("tosin/LLaDoc") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use tosin/LLaDoc with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tosin/LLaDoc" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tosin/LLaDoc", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tosin/LLaDoc
- SGLang
How to use tosin/LLaDoc with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "tosin/LLaDoc" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tosin/LLaDoc", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "tosin/LLaDoc" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tosin/LLaDoc", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tosin/LLaDoc with Docker Model Runner:
docker model run hf.co/tosin/LLaDoc
Created README
Browse files
README.md
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---
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thumbnail: https://huggingface.co/front/thumbnails/lladoc.png
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language:
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- en
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license: cc-by-4.0
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tags:
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- transformers
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datasets:
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- idocvqa
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metrics:
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- accuracy
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---
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## LLaDoc (Large Language and Document) model
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This is a fine-tuned model of LLaVA1.5 (7B) on the iDocVQA dataset. It is intended to be used as a multimodal system.
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The dataset it's trained on is limited in scope, as it covers only certain domains.
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The accuracy achieved on the validation set is 29.58%.
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Please find the information about preprocessing, training and full details of the LLaVA model in the [original link](https://llava-vl.github.io/)
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The paper for this work is available on arXiv: [https://arxiv.org/abs/2402.00453](https://arxiv.org/abs/2402.00453)
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