This is the first 4 layers of DeepSeek-V3 with GPTQ quantization style.
- Layer 4's all routed experts (256 experts) are quantized to 2-bit
- All other Linear layers are quantized to 4-bit (including MLA, dense layer ffn, and shared expert)
To load and run this model:
from transformers import AutoModelForCausalLM, AutoTokenizer
from gptqmodel import GPTQModel, QuantizeConfig, get_best_device
pretrained_model_id = "/root/dataDisk/DeepSeek-V3-bf16-4layers"
quantized_model_id = "/root/dataDisk/DeepSeek-V3-4bit-4layers"
tokenizer = AutoTokenizer.from_pretrained(pretrained_model_id, use_fast=True)
device = get_best_device()
model = GPTQModel.load(quantized_model_id, device=device, trust_remote_code=True)
print(tokenizer.decode(model.generate(**tokenizer("gptqmodel is", return_tensors="pt").to(model.device), max_new_tokens=10)[0]))
- Downloads last month
- 12
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no library tag.
Model tree for tflsxyy/DeepSeek-V3-4bit-4layers
Base model
deepseek-ai/DeepSeek-V3