Instructions to use stepprog/qwen3-4b-math-lora3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use stepprog/qwen3-4b-math-lora3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("RefalMachine/RuadaptQwen3-4B-Hybrid") model = PeftModel.from_pretrained(base_model, "stepprog/qwen3-4b-math-lora3") - Transformers
How to use stepprog/qwen3-4b-math-lora3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="stepprog/qwen3-4b-math-lora3") 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("stepprog/qwen3-4b-math-lora3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use stepprog/qwen3-4b-math-lora3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stepprog/qwen3-4b-math-lora3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stepprog/qwen3-4b-math-lora3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/stepprog/qwen3-4b-math-lora3
- SGLang
How to use stepprog/qwen3-4b-math-lora3 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 "stepprog/qwen3-4b-math-lora3" \ --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": "stepprog/qwen3-4b-math-lora3", "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 "stepprog/qwen3-4b-math-lora3" \ --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": "stepprog/qwen3-4b-math-lora3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use stepprog/qwen3-4b-math-lora3 with Docker Model Runner:
docker model run hf.co/stepprog/qwen3-4b-math-lora3
Download tokenizer_config.json from stepprog/qwen3-4b-math-lora3: direct link, hf CLI and curl.
- Browser
- Download file 9.25 kB
-
https://huggingface.co/stepprog/qwen3-4b-math-lora3/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://stepprog/qwen3-4b-math-lora3/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/stepprog/qwen3-4b-math-lora3/resolve/main/tokenizer_config.json
9.25 kB
| { | |
| "add_bos_token": false, | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
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| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
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| "single_word": false, | |
| "special": true | |
| }, | |
| "146214": { | |
| "content": "<|im_start|>", | |
| "lstrip": false, | |
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| "single_word": false, | |
| "special": true | |
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| "146215": { | |
| "content": "<|im_end|>", | |
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| "146257": { | |
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| "special": false | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<|object_ref_start|>", | |
| "<|object_ref_end|>", | |
| "<|box_start|>", | |
| "<|box_end|>", | |
| "<|quad_start|>", | |
| "<|quad_end|>", | |
| "<|vision_start|>", | |
| "<|vision_end|>", | |
| "<|vision_pad|>", | |
| "<|image_pad|>", | |
| "<|video_pad|>" | |
| ], | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "extra_special_tokens": {}, | |
| "model_max_length": 40960, | |
| "pad_token": "<|endoftext|>", | |
| "padding_side": "right", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |