Text Generation
Transformers
Safetensors
phi-msft
Merge
mergekit
lazymergekit
rhysjones/phi-2-orange
cognitivecomputations/dolphin-2_6-phi-2
Microsoft/Phi-2
custom_code
Instructions to use Venkman42/Phiter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Venkman42/Phiter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Venkman42/Phiter", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Venkman42/Phiter", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Venkman42/Phiter with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Venkman42/Phiter" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Venkman42/Phiter", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Venkman42/Phiter
- SGLang
How to use Venkman42/Phiter 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 "Venkman42/Phiter" \ --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": "Venkman42/Phiter", "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 "Venkman42/Phiter" \ --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": "Venkman42/Phiter", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Venkman42/Phiter with Docker Model Runner:
docker model run hf.co/Venkman42/Phiter
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# Phiter
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6493317e9621f988db6c469c/ZjXk8XIDt00E2n6j4brQW.png" alt="
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Phiter is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [rhysjones/phi-2-orange](https://huggingface.co/rhysjones/phi-2-orange)
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# Phiter
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6493317e9621f988db6c469c/ZjXk8XIDt00E2n6j4brQW.png" alt="Phiter Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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Phiter is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [rhysjones/phi-2-orange](https://huggingface.co/rhysjones/phi-2-orange)
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