Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

inclusionAI
/
Ming-Lite-Omni

Any-to-Any
Transformers
ONNX
Diffusers
Safetensors
bailingmm
text-generation
custom_code
Model card Files Files and versions
xet
Community
6

Instructions to use inclusionAI/Ming-Lite-Omni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use inclusionAI/Ming-Lite-Omni with Transformers:

    # Load model directly
    from transformers import AutoModelForSeq2SeqLM
    model = AutoModelForSeq2SeqLM.from_pretrained("inclusionAI/Ming-Lite-Omni", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

model load and infer

#6 opened 11 months ago by
yy

Does this model have a RAG?

1
#5 opened 11 months ago by
thatC0d3rii

Request for quantized version for 24GB VRAM (and also a gradio GUI demo script)

1
#4 opened 11 months ago by
mingyi456

Inquiry about Future Plans for Releasing Ming-Omni Training Data

1
#3 opened 12 months ago by
Vegetaking

Colab notebook to run the model?

➕👀 3
6
#1 opened 12 months ago by
amgadhasan
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs