Text Generation
Transformers
Safetensors
phi-msft
Merge
mergekit
lazymergekit
rhysjones/phi-2-orange
cognitivecomputations/dolphin-2_6-phi-2
mrm8488/phi-2-coder
custom_code
Instructions to use Isotonic/phizzle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isotonic/phizzle with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Isotonic/phizzle", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Isotonic/phizzle", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Isotonic/phizzle with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Isotonic/phizzle" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Isotonic/phizzle", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Isotonic/phizzle
- SGLang
How to use Isotonic/phizzle 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 "Isotonic/phizzle" \ --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": "Isotonic/phizzle", "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 "Isotonic/phizzle" \ --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": "Isotonic/phizzle", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Isotonic/phizzle with Docker Model Runner:
docker model run hf.co/Isotonic/phizzle
Upload folder using huggingface_hub
Browse files- README.md +4 -5
- mergekit_config.yml +1 -1
README.md
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- merge
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- mergekit
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- lazymergekit
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- cognitivecomputations/dolphin-2_6-phi-2
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- mrm8488/phi-2-coder
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- rhysjones/phi-2-orange
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---
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# phi-2-ties
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phi-2-ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [cognitivecomputations/dolphin-2_6-phi-2](https://huggingface.co/cognitivecomputations/dolphin-2_6-phi-2)
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* [mrm8488/phi-2-coder](https://huggingface.co/mrm8488/phi-2-coder)
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* [rhysjones/phi-2-orange](https://huggingface.co/rhysjones/phi-2-orange)
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## 🧩 Configuration
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- model: rhysjones/phi-2-orange
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parameters:
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density: 0.5
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weight: 0.
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- model: cognitivecomputations/dolphin-2_6-phi-2
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parameters:
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density: 0.5
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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trust_remote_code=True
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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- merge
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- mergekit
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- lazymergekit
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+
- rhysjones/phi-2-orange
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- cognitivecomputations/dolphin-2_6-phi-2
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- mrm8488/phi-2-coder
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---
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# phi-2-ties
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phi-2-ties 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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* [cognitivecomputations/dolphin-2_6-phi-2](https://huggingface.co/cognitivecomputations/dolphin-2_6-phi-2)
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* [mrm8488/phi-2-coder](https://huggingface.co/mrm8488/phi-2-coder)
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## 🧩 Configuration
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- model: rhysjones/phi-2-orange
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parameters:
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density: 0.5
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weight: 0.3
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- model: cognitivecomputations/dolphin-2_6-phi-2
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parameters:
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density: 0.5
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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mergekit_config.yml
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- model: rhysjones/phi-2-orange
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parameters:
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density: 0.5
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weight: 0.
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- model: cognitivecomputations/dolphin-2_6-phi-2
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parameters:
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density: 0.5
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- model: rhysjones/phi-2-orange
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parameters:
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density: 0.5
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weight: 0.3
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- model: cognitivecomputations/dolphin-2_6-phi-2
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parameters:
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density: 0.5
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