Instructions to use if001/sample_phi-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use if001/sample_phi-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="if001/sample_phi-2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("if001/sample_phi-2") model = AutoModelForCausalLM.from_pretrained("if001/sample_phi-2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use if001/sample_phi-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "if001/sample_phi-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "if001/sample_phi-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/if001/sample_phi-2
- SGLang
How to use if001/sample_phi-2 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 "if001/sample_phi-2" \ --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": "if001/sample_phi-2", "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 "if001/sample_phi-2" \ --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": "if001/sample_phi-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use if001/sample_phi-2 with Docker Model Runner:
docker model run hf.co/if001/sample_phi-2
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README.md
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license: mit
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---
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PhiConfig {
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"use_cache": true,
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"vocab_size": 20
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}
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PhiForCausalLM(
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(model): PhiModel(
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(embed_tokens): Embedding(20, 8)
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)
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(lm_head): Linear(in_features=8, out_features=20, bias=True)
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)
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===========================================================================
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Layer (type:depth-idx) Param #
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===========================================================================
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Total params: 2,816
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Trainable params: 2,816
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Non-trainable params: 0
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===========================================================================
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license: mit
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---
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```
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PhiConfig {
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"use_cache": true,
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"vocab_size": 20
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}
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```
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```
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PhiForCausalLM(
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(model): PhiModel(
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(embed_tokens): Embedding(20, 8)
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)
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(lm_head): Linear(in_features=8, out_features=20, bias=True)
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)
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```
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```
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===========================================================================
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Layer (type:depth-idx) Param #
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===========================================================================
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Total params: 2,816
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Trainable params: 2,816
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Non-trainable params: 0
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===========================================================================
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```
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