Instructions to use asw97/TM10545-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asw97/TM10545-parser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="asw97/TM10545-parser")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("asw97/TM10545-parser") model = AutoModelForMultimodalLM.from_pretrained("asw97/TM10545-parser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use asw97/TM10545-parser with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "asw97/TM10545-parser" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "asw97/TM10545-parser", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/asw97/TM10545-parser
- SGLang
How to use asw97/TM10545-parser 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 "asw97/TM10545-parser" \ --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": "asw97/TM10545-parser", "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 "asw97/TM10545-parser" \ --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": "asw97/TM10545-parser", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use asw97/TM10545-parser with Docker Model Runner:
docker model run hf.co/asw97/TM10545-parser
Training finished
Browse files- added_tokens.json +1 -17
- tokenizer.json +0 -144
added_tokens.json
CHANGED
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{
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"</s_caption_number>": 57536,
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"</s_captions>": 57534,
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"</s_component>": 57538,
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"</s_component_detail>": 57540,
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"</s_compontent_name>": 57542,
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"</s_instruction>": 57530,
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"</s_repair_steps>": 57526,
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"</s_specifications>": 57532,
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"</s_step_number>": 57528,
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"<
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"</s_subtitles>": 57544,
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"<s_10545>": 57547,
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"<s_caption_number>": 57535,
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"<s_captions>": 57533,
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"<s_component>": 57537,
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"<s_component_detail>": 57539,
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"<s_compontent_name>": 57541,
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"<s_iitcdip>": 57523,
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"<s_instruction>": 57529,
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"<s_repair_steps>": 57525,
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"<s_specifications>": 57531,
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"<s_step_number>": 57527,
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"<s_subtitle>": 57545,
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"<s_subtitles>": 57543,
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"<s_synthdog>": 57524,
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"<sep/>": 57522
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}
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"</s_instruction>": 57530,
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"</s_repair_steps>": 57526,
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"</s_step_number>": 57528,
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"<s_10545>": 57531,
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"<s_iitcdip>": 57523,
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"<s_instruction>": 57529,
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"<s_repair_steps>": 57525,
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"<s_step_number>": 57527,
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"<s_synthdog>": 57524,
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"<sep/>": 57522
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}
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tokenizer.json
CHANGED
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},
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"id": 57531,
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"single_word": false,
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"lstrip": false,
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"normalized": true,
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"id": 57545,
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"content": "<s_subtitle>",
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{
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"id": 57546,
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{
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"id": 57547,
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"content": "<s_10545>",
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"single_word": false,
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"lstrip": false,
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},
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{
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"id": 57531,
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"content": "<s_10545>",
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"single_word": false,
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"lstrip": false,
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