Text Generation
Transformers
Safetensors
Korean
English
keural
mixtral
Mixture of Experts
korean
bilingual
causal-lm
dpo
rlhf
instruction-tuned
chat
conversational
custom_code
Instructions to use mkd-hossain/keural-dpo-5500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkd-hossain/keural-dpo-5500 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mkd-hossain/keural-dpo-5500", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mkd-hossain/keural-dpo-5500", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mkd-hossain/keural-dpo-5500 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mkd-hossain/keural-dpo-5500" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mkd-hossain/keural-dpo-5500", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/mkd-hossain/keural-dpo-5500
- SGLang
How to use mkd-hossain/keural-dpo-5500 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 "mkd-hossain/keural-dpo-5500" \ --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": "mkd-hossain/keural-dpo-5500", "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 "mkd-hossain/keural-dpo-5500" \ --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": "mkd-hossain/keural-dpo-5500", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use mkd-hossain/keural-dpo-5500 with Docker Model Runner:
docker model run hf.co/mkd-hossain/keural-dpo-5500
- Xet hash:
- 327a100f449217ac9047c792ea6a4eade6bfca7b1209268a9ff66a39effe1fe1
- Size of remote file:
- 4.81 GB
- SHA256:
- 1d5d4721eece97213f5a836e6bc8fd55c8d4e2ef7a2e3eccb4537bc7e2809574
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