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frankdarkluo/DeepSeek-R1-Distill-Qwen-32B-GPTQ-Int8
DeepSeek-R1-Distill-Qwen-32B-GPTQ-Int8 is a text generation model from frankdarkluo. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
See details on the official page of the model: DeepSeek-R1-Distill-Qwen-32B
Downloads · 30 days
39
1% of all-time downloads
All-time downloads
3.7K
Public
Parameters
32.8B
35.1 GB on disk
Likes
2
Public
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.safetensors35.1 GB · 100%
How the weights are stored.
I3231.2B · 95%
From the Hugging Face model README
See details on the official page of the model: DeepSeek-R1-Distill-Qwen-32B
Quantized using GPTQModel using Allenai/C4 dataset. Quantization config:
bits=8,
group_size=128,
desc_act=False,
Using transformers library with integrated GPTQ support:
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
model_name = "frankdarkluo/DeepSeek-R1-Distill-Qwen-32B-GPTQ-Int8"
tokenizer = AutoTokenizer.from_pretrained(model_name)
quantized_model = AutoModelForCausalLM.from_pretrained(model_name, device_map='cuda')
chat = [{"role": "user", "content": "Why is grass green?"},]
question_tokens = tokenizer.apply_chat_template(chat, add_generation_prompt=True, return_tensors="pt").to(quantized_model.device)
answer_tokens = quantized_model.generate(question_tokens, generation_config=GenerationConfig(max_length=2048, ))[0]
print(tokenizer.decode(answer_tokens))