Instructions to use amphora/small-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amphora/small-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="amphora/small-instruct")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("amphora/small-instruct") model = AutoModelForCausalLM.from_pretrained("amphora/small-instruct") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use amphora/small-instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "amphora/small-instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "amphora/small-instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/amphora/small-instruct
- SGLang
How to use amphora/small-instruct 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 "amphora/small-instruct" \ --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": "amphora/small-instruct", "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 "amphora/small-instruct" \ --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": "amphora/small-instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use amphora/small-instruct with Docker Model Runner:
docker model run hf.co/amphora/small-instruct
File size: 1,674 Bytes
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"rstrip": false,
"single_word": false,
"special": true
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"50261": {
"content": "</s>",
"lstrip": false,
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"rstrip": false,
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"<|endoftext|>",
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"<s>",
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"<unk>"
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"bos_token": "<s>",
"clean_up_tokenization_spaces": true,
"eos_token": "</s>",
"errors": "replace",
"model_max_length": 8192,
"pad_token": "<||pad||>",
"tokenizer_class": "GPT2Tokenizer",
"unk_token": "<unk>"
}
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