Instructions to use xhyi/CodeGen-2B-Multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xhyi/CodeGen-2B-Multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="xhyi/CodeGen-2B-Multi", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("xhyi/CodeGen-2B-Multi", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("xhyi/CodeGen-2B-Multi", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use xhyi/CodeGen-2B-Multi with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "xhyi/CodeGen-2B-Multi" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "xhyi/CodeGen-2B-Multi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/xhyi/CodeGen-2B-Multi
- SGLang
How to use xhyi/CodeGen-2B-Multi 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 "xhyi/CodeGen-2B-Multi" \ --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": "xhyi/CodeGen-2B-Multi", "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 "xhyi/CodeGen-2B-Multi" \ --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": "xhyi/CodeGen-2B-Multi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use xhyi/CodeGen-2B-Multi with Docker Model Runner:
docker model run hf.co/xhyi/CodeGen-2B-Multi
add tokenizer
Browse files- added_tokens.json +1 -0
- merges.txt +0 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.json +0 -0
added_tokens.json
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{" ": 50257, " ": 50258, " ": 50259, " ": 50260, " ": 50261, " ": 50262, " ": 50263, " ": 50264, " ": 50265, " ": 50266, " ": 50267, " ": 50268, " ": 50269, " ": 50270, " ": 50271, " ": 50272, " ": 50273, " ": 50274, " ": 50275, " ": 50276, " ": 50277, " ": 50278, " ": 50279, " ": 50280, " ": 50281, " ": 50282, " ": 50283, " ": 50284, " ": 50285, " ": 50286, "\t\t\t\t\t\t\t\t\t": 50287, "\t\t\t\t\t\t\t\t": 50288, "\t\t\t\t\t\t\t": 50289, "\t\t\t\t\t\t": 50290, "\t\t\t\t\t": 50291, "\t\t\t\t": 50292, "\t\t\t": 50293, "\t\t": 50294, "50256": 50295}
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merges.txt
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special_tokens_map.json
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{"bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "unk_token": "<|endoftext|>", "pad_token": 50256}
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tokenizer_config.json
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{"errors": "replace", "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "PT_SFCodeGen_2B", "trust_remote_code": true, "tokenizer_class": "GPT2Tokenizer"}
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vocab.json
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