canxp-ai/qwen36-m1-validation-v14-05174e06
05
qwen36-m1-validation-v14
Fine-tuned by CanXP AI (canxp.ai) from base model Qwen/Qwen3.6-27B using QLORA.
Quick start (Python)
pip install transformers peft torchfrom transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
base = "Qwen/Qwen3.6-27B"
adapter = "canxp-ai/qwen36-m1-validation-v14-05174e06"
tokenizer = AutoTokenizer.from_pretrained(base, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
base, torch_dtype="bfloat16", device_map="auto", trust_remote_code=True
)
model = PeftModel.from_pretrained(model, adapter)
prompt = "Hello!"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(out[0], skip_special_tokens=True))CLI download
pip install -U "huggingface_hub[cli]"
huggingface-cli download canxp-ai/qwen36-m1-validation-v14-05174e06 --local-dir ./qwen36-m1-validation-v14Training details
- Base model:
Qwen/Qwen3.6-27B - Method: QLORA
- Epochs: 1
- Context length: 2048
- Validation split: 0.1
This adapter inherits the upstream license of the base model. See LICENSE_NOTICE.txt in this repo for details.
