Text Generation
Transformers
Safetensors
PEFT
English
emotion-classification
mental-health
llama-3.1
unsloth
lora
conversational
Instructions to use RockyBai/Mirari with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RockyBai/Mirari with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="RockyBai/Mirari") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RockyBai/Mirari", device_map="auto") - PEFT
How to use RockyBai/Mirari with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use RockyBai/Mirari with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RockyBai/Mirari" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RockyBai/Mirari", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/RockyBai/Mirari
- SGLang
How to use RockyBai/Mirari 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 "RockyBai/Mirari" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RockyBai/Mirari", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "RockyBai/Mirari" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RockyBai/Mirari", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use RockyBai/Mirari with Docker Model Runner:
docker model run hf.co/RockyBai/Mirari
Commit History
-
Update README.md
Verified signature94ec26f -
Upload adapter_model.safetensors
Verified signature0063c02 -
Upload 7 files
Verified signature88eb26c -
Upload tokenizer_config.json
Verified signature0f07609 -
Upload chat_template.jinja
Verified signature3362cfd -
Upload README.md
Verified signature479ced2 -
Upload special_tokens_map.json
Verified signaturec45ac55 -
Upload training_config.json
Verified signature8587ca1 -
Upload adapter_config.json with huggingface_hub
Verified signature98f5fca -
Upload README.md with huggingface_hub
Verified signatured52625a -
initial commit
Verified signature22935a1