Instructions to use MJ199999/gpt3_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MJ199999/gpt3_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MJ199999/gpt3_model")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MJ199999/gpt3_model") model = AutoModelForCausalLM.from_pretrained("MJ199999/gpt3_model") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MJ199999/gpt3_model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MJ199999/gpt3_model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MJ199999/gpt3_model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MJ199999/gpt3_model
- SGLang
How to use MJ199999/gpt3_model 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 "MJ199999/gpt3_model" \ --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": "MJ199999/gpt3_model", "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 "MJ199999/gpt3_model" \ --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": "MJ199999/gpt3_model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MJ199999/gpt3_model with Docker Model Runner:
docker model run hf.co/MJ199999/gpt3_model
add tokenizer
Browse files- added_tokens.json +4 -0
- merges.txt +0 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +10 -0
- vocab.json +0 -0
added_tokens.json
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{
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"newWord": 51200,
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"newWord2": 51201
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}
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merges.txt
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special_tokens_map.json
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{
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"bos_token": "</s>",
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"eos_token": "</s>",
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"mask_token": "<mask>",
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"bos_token": "</s>",
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"eos_token": "</s>",
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"name_or_path": "skt/ko-gpt-trinity-1.2B-v0.5",
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"pad_token": "<pad>",
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"special_tokens_map_file": "/root/.cache/huggingface/transformers/c2ab65b9d700d0871fd407d489869d7b93f69fb5f1a58fb1fac796fd43b9ea27.1f5b09bb43973b9fbd2ba75c9fe44ffab036b980c4e6a9d779aa7707913416fe",
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": "<|endoftext|>"
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}
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vocab.json
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