Instructions to use cipher982/report_builder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cipher982/report_builder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cipher982/report_builder")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("cipher982/report_builder") model = AutoModelForCausalLM.from_pretrained("cipher982/report_builder") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use cipher982/report_builder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cipher982/report_builder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cipher982/report_builder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/cipher982/report_builder
- SGLang
How to use cipher982/report_builder 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 "cipher982/report_builder" \ --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": "cipher982/report_builder", "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 "cipher982/report_builder" \ --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": "cipher982/report_builder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use cipher982/report_builder with Docker Model Runner:
docker model run hf.co/cipher982/report_builder
Upload tokenizer
Browse files- added_tokens.json +3 -0
- special_tokens_map.json +4 -1
- tokenizer.json +27 -0
added_tokens.json
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{
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"<END_A>": 32003,
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"<END_Q>": 32001,
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"<START_A>": 32002,
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"<START_Q>": 32000
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}
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{
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"<ASC>": 32006,
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"<DIM>": 32004,
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"<END_A>": 32003,
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"<END_Q>": 32001,
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"<MET>": 32005,
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"<START_A>": 32002,
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"<START_Q>": 32000
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}
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special_tokens_map.json
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"<START_Q>",
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"<END_Q>",
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"<START_A>",
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"<END_A>"
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],
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"bos_token": {
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"content": "<s>",
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"<START_Q>",
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"<END_Q>",
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"<START_A>",
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"<END_A>",
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"<DIM>",
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"<MET>",
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"<ASC>"
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],
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"bos_token": {
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"content": "<s>",
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tokenizer.json
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"rstrip": false,
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"normalized": false,
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"special": true
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}
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],
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"normalizer": {
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"rstrip": false,
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"normalized": false,
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"special": true
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},
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{
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"id": 32004,
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"content": "<DIM>",
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"single_word": false,
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"lstrip": false,
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"rstrip": false,
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"normalized": false,
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"special": true
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},
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{
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"id": 32005,
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"content": "<MET>",
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"single_word": false,
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"lstrip": false,
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"rstrip": false,
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"normalized": false,
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"special": true
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},
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{
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"id": 32006,
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"content": "<ASC>",
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"single_word": false,
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"lstrip": false,
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"rstrip": false,
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"normalized": false,
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"special": true
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}
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],
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"normalizer": {
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