✍️ Text Generation

DeepSeek-V3.2

deepseek-ai/DeepSeek-V3.2

Get AI Model →
10.4M
Downloads
❤️
1.4K
Likes
🏷️
11
Tags
📦
transformers
Library
Model Details
Full Model IDdeepseek-ai/DeepSeek-V3.2
Pipeline / Tasktext-generation
Librarytransformers
Downloads (all-time)10.4M
Likes1.4K
Last Modified12/1/2025
Author / Orgdeepseek-ai
PrivateNo — public
⚡ Quick Usage (Python)

Using the 🤗 Transformers library. Install with pip install transformers

from transformers import pipeline

# Load the model
pipe = pipeline("text-generation", model="deepseek-ai/DeepSeek-V3.2")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerssafetensorsdeepseek_v32text-generationbase_model:deepseek-ai/DeepSeek-V3.2-Exp-Basebase_model:finetune:deepseek-ai/DeepSeek-V3.2-Exp-Baselicense:miteval-resultsendpoints_compatiblefp8region:us
More Text Generation Models
See all →
Qwen3-0.6B

Qwen/Qwen3-0.6B

16.1M❤️ 1.2K
Get AI Model →
gpt2

openai-community/gpt2

14.0M❤️ 3.2K
Get AI Model →
Qwen2.5-7B-Instruct

Qwen/Qwen2.5-7B-Instruct

12.3M❤️ 1.2K
Get AI Model →
🚀 Use This Model

Access model files, inference API, and full documentation on Hugging Face.

Open on Hugging Face →Browse Model Files ↗← Browse All Models
✍️ Task: Text Generation

This model is designed for the Text Generation task. Explore more models for this use case.

All Text Generation Models →
📊 Popularity
Downloads10.4M
❤️ Community Likes1.4K
🛠️ Requirements
  • Install: pip install transformers
  • Python 3.8+ recommended for Transformers.
  • GPU (CUDA) speeds up inference significantly.
  • Use model.half() for fp16 on limited VRAM.
👋 Need help with code?