How to use from
Unsloth StudioInstall Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Jake5/Qwen2.5-Coder-32B-Instruct-WMX to start chattingUsing HuggingFace Spaces for Unsloth
# No setup required# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Jake5/Qwen2.5-Coder-32B-Instruct-WMX to start chattingLoad model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="Jake5/Qwen2.5-Coder-32B-Instruct-WMX",
max_seq_length=2048,
)Quick Links
Qwen2.5-Coder-32B-Instruct-WMX
Pre-fine-tuned LoRA adapters for unsloth/Qwen2.5-Coder-32B-Instruct.
This lora adapters have been fine-tuned for WMX services using the folowing datasets.
- https://huggingface.co/datasets/Jake5/movensys-info
- https://huggingface.co/datasets/Jake5/wmx-doc-user
- https://huggingface.co/datasets/Jake5/wmx-doc-robot
Version v0.9
- Source: lora_model
- Base model: unsloth/Qwen2.5-Coder-32B-Instruct
- Uploaded on: 2025-09-12
Usage
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-32B-Instruct")
model = PeftModel.from_pretrained(base_model, "Jake5/Qwen2.5-Coder-32B-Instruct-WMX", subfolder="adapters_v0.9")
tokenizer = AutoTokenizer.from_pretrained("Jake5/Qwen2.5-Coder-32B-Instruct-WMX", subfolder="adapters_v0.9")
vLLM Serving
python -m vllm.entrypoints.openai.api_server \
--model unsloth/Qwen2.5-Coder-32B-Instruct \
--lora-modules my-lora=Jake5/Qwen2.5-Coder-32B-Instruct-WMX/adapters_v0.9 \
--dtype bfloat16 \
--port 8000
Inference Providers NEW
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Model tree for Jake5/Qwen2.5-Coder-32B-Instruct-WMX
Base model
Qwen/Qwen2.5-32B Finetuned
Qwen/Qwen2.5-Coder-32B Finetuned
Qwen/Qwen2.5-Coder-32B-Instruct
Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Jake5/Qwen2.5-Coder-32B-Instruct-WMX to start chatting