Instructions to use unamedai/KateAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unamedai/KateAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="unamedai/KateAI")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("unamedai/KateAI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use unamedai/KateAI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unamedai/KateAI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unamedai/KateAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/unamedai/KateAI
- SGLang
How to use unamedai/KateAI 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 "unamedai/KateAI" \ --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": "unamedai/KateAI", "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 "unamedai/KateAI" \ --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": "unamedai/KateAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use unamedai/KateAI with Docker Model Runner:
docker model run hf.co/unamedai/KateAI
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language:
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pipeline_tag: text-generation
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---
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#
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This model is in the process of being moved from gpt2 architecture -> a custom architecture.
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Note that it may not work at certain times because of the moving.
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Thank you for understanding.
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# Kate
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This is a custom model for text generation.
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Money wasted: 11€
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## Model Details
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- `model_type`: KateAIForCasualLM
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## Usage
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Please use the api of the space.
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```
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pip install gradio_client
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```
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```
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from gradio_client import Client
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client = Client("unamedai/Kate")
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result = client.predict(
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message="Once,",
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max_tokens=512,
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temperature=0.8,
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top_p=0.95,
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api_name="/predict"
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)
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print(result)
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```
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language:
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pipeline_tag: text-generation
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license: mit
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base_model:
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- Qwen/Qwen3-14B
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tags:
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- Conzola
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- Kate
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- cLongBar
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- '#cForTheBetter'
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---
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### Documentation is coming soon...
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