Instructions to use emre/llama-2-13b-code-122k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emre/llama-2-13b-code-122k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="emre/llama-2-13b-code-122k")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("emre/llama-2-13b-code-122k") model = AutoModelForCausalLM.from_pretrained("emre/llama-2-13b-code-122k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use emre/llama-2-13b-code-122k with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "emre/llama-2-13b-code-122k" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "emre/llama-2-13b-code-122k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/emre/llama-2-13b-code-122k
- SGLang
How to use emre/llama-2-13b-code-122k 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 "emre/llama-2-13b-code-122k" \ --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": "emre/llama-2-13b-code-122k", "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 "emre/llama-2-13b-code-122k" \ --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": "emre/llama-2-13b-code-122k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use emre/llama-2-13b-code-122k with Docker Model Runner:
docker model run hf.co/emre/llama-2-13b-code-122k
Commit History
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (1438243d5c1c5bc2eee060be765ac4370d48bd85) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>7ef9650
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Create README.md
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Upload events.out.tfevents.1690764614.cab9e34f3056.2539.1
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Upload tokenizer
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Upload LlamaForCausalLM
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initial commit
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