Text Generation
Transformers
Safetensors
PyTorch
English
logos
causal-lm
custom-code
base-model
custom_code
Instructions to use Rorical/logos-1b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rorical/logos-1b-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Rorical/logos-1b-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Rorical/logos-1b-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Rorical/logos-1b-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Rorical/logos-1b-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Rorical/logos-1b-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Rorical/logos-1b-base
- SGLang
How to use Rorical/logos-1b-base 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 "Rorical/logos-1b-base" \ --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": "Rorical/logos-1b-base", "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 "Rorical/logos-1b-base" \ --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": "Rorical/logos-1b-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Rorical/logos-1b-base with Docker Model Runner:
docker model run hf.co/Rorical/logos-1b-base
Upload models/__init__.py
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from .baseline import BaselineConfig, BaselineTransformer
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from .linear import LinearConfig, LinearTransformer
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from .recursive import RecursiveConfig, RecursiveTransformer
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from .residual import ResidualConfig, ResidualTransformer
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from .hybrid import HybridConfig, HybridTransformer
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from .logos import LogosConfig, LogosTransformer
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__all__ = [
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"BaselineConfig",
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"BaselineTransformer",
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"LinearConfig",
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"LinearTransformer",
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"RecursiveConfig",
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"RecursiveTransformer",
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"ResidualConfig",
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"ResidualTransformer",
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"HybridConfig",
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"HybridTransformer",
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"LogosConfig",
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"LogosTransformer",
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]
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