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Sponsored by
AdsCreator.com
ModelCloud / QwQ-32B-Preview-gptqmodel-4bit-vortex-v2
Model's Last Updated: December 18 2024
text-generation
Introduction of QwQ-32B-Preview-gptqmodel-4bit-vortex-v2
Model Details of QwQ-32B-Preview-gptqmodel-4bit-vortex-v2
This model has been quantized using GPTQModel .
- bits : 4
- dynamic : null
- group_size : 32
- desc_act : true
- static_groups : false
- sym : true
- lm_head : false
- true_sequential : true
- quant_method : "gptq"
- checkpoint_format : "gptq"
-
meta
：
- quantizer : gptqmodel:1.4.4
- uri : https://github.com/modelcloud/gptqmodel
- damp_percent : 0.1
- damp_auto_increment : 0.0015
Example:
from transformers import AutoTokenizer
from gptqmodel import GPTQModel
tokenizer = AutoTokenizer.from_pretrained("ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v2")
model = GPTQModel.load("ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v2")
messages = [
{"role": "system", "content": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step."},
{"role": "user", "content": "How can I design a data structure in C++ to store the top 5 largest integer numbers?"},
]
input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")
outputs = model.generate(input_ids=input_tensor.to(model.device), max_new_tokens=512)
result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True)
print(result)
Runs of ModelCloud QwQ-32B-Preview-gptqmodel-4bit-vortex-v2 on huggingface.co
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More Information About QwQ-32B-Preview-gptqmodel-4bit-vortex-v2 huggingface.co Model
Url of QwQ-32B-Preview-gptqmodel-4bit-vortex-v2
QwQ-32B-Preview-gptqmodel-4bit-vortex-v2 huggingface.co Url
Provider of QwQ-32B-Preview-gptqmodel-4bit-vortex-v2 huggingface.co
Other API from ModelCloud
Updated:February 07 2025
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