Instructions to use MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MagistrTheOne/KNK-VF-Lab-38B") model = PeftModel.from_pretrained(base_model, "MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA") - Transformers
How to use MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA
- SGLang
How to use MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA 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 "MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA" \ --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": "MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA", "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 "MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA" \ --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": "MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA with Docker Model Runner:
docker model run hf.co/MagistrTheOne/KUROTAMA-KNK-VF-Lab38B-SFT-LoRA
| { | |
| "add_prefix_space": null, | |
| "backend": "tokenizers", | |
| "bos_token": "<|bos|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|eos|>", | |
| "extra_special_tokens": [ | |
| "<|system|>", | |
| "<|user|>", | |
| "<|assistant|>", | |
| "<|tool|>", | |
| "<|code|>", | |
| "<|/code|>", | |
| "<|think|>", | |
| "<|/think|>" | |
| ], | |
| "is_local": true, | |
| "local_files_only": false, | |
| "model_max_length": 131072, | |
| "pad_token": "<|pad|>", | |
| "padding_side": "right", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "LlamaTokenizer", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |