Instructions to use inclusionAI/Ring-1T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/Ring-1T with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="inclusionAI/Ring-1T", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("inclusionAI/Ring-1T", trust_remote_code=True, dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use inclusionAI/Ring-1T with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "inclusionAI/Ring-1T" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inclusionAI/Ring-1T", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/inclusionAI/Ring-1T
- SGLang
How to use inclusionAI/Ring-1T with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "inclusionAI/Ring-1T" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inclusionAI/Ring-1T", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "inclusionAI/Ring-1T" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inclusionAI/Ring-1T", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use inclusionAI/Ring-1T with Docker Model Runner:
docker model run hf.co/inclusionAI/Ring-1T
Openmodel shares your model under its own name without forking it and claims to have built it from scratch.
Thanks for letting us know. It does look very... similar... to Ling-1T...
You can report :)
Even the SHA256 hashes of the safetensors are the same, it's a straight copy-paste job.
https://huggingface.co/inclusionAI/Ling-1T/blob/main/model-00001-of-00155.safetensors
SHA256: 02b5cbbf76f7b21e54a936db254aef54aa4196d8a729c93ce6e26e7467c9448c
https://huggingface.co/thenexthub/OpenModel-1T-A50B-Instruct/blob/main/model-00001-of-00155.safetensors
SHA256: 02b5cbbf76f7b21e54a936db254aef54aa4196d8a729c93ce6e26e7467c9448c
https://huggingface.co/inclusionAI/Ling-1T/blob/main/model-00002-of-00155.safetensors
SHA256: 8bd28b5ae46d9bfd9a606fb9a3d78145a82ccc683cba6046d0778c5cff62774b
https://huggingface.co/thenexthub/OpenModel-1T-A50B-Instruct/blob/main/model-00002-of-00155.safetensors
SHA256: 8bd28b5ae46d9bfd9a606fb9a3d78145a82ccc683cba6046d0778c5cff62774b
Yes, please report it