Text Generation
Transformers
PyTorch
Safetensors
English
rubirlm
causal-lm
base-model
1b
Mixture of Experts
Instructions to use DevHunterAI/RubiRLM-1B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DevHunterAI/RubiRLM-1B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DevHunterAI/RubiRLM-1B-Base")# Load model directly from transformers import RubiRLM model = RubiRLM.from_pretrained("DevHunterAI/RubiRLM-1B-Base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DevHunterAI/RubiRLM-1B-Base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DevHunterAI/RubiRLM-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": "DevHunterAI/RubiRLM-1B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DevHunterAI/RubiRLM-1B-Base
- SGLang
How to use DevHunterAI/RubiRLM-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 "DevHunterAI/RubiRLM-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": "DevHunterAI/RubiRLM-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 "DevHunterAI/RubiRLM-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": "DevHunterAI/RubiRLM-1B-Base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DevHunterAI/RubiRLM-1B-Base with Docker Model Runner:
docker model run hf.co/DevHunterAI/RubiRLM-1B-Base
- Xet hash:
- 725e3cafac69bb511983b275ab9319c128da4f12b5a35a5d7aef4dc6bf5291fe
- Size of remote file:
- 3.95 GB
- SHA256:
- 1a37b2fb3ddad5d668ad951b160851b35536b203d1f51213a1c34f72b6308d48
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