Instructions to use tngtech/DeepSeek-R1T-Chimera with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tngtech/DeepSeek-R1T-Chimera with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tngtech/DeepSeek-R1T-Chimera", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tngtech/DeepSeek-R1T-Chimera", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("tngtech/DeepSeek-R1T-Chimera", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use tngtech/DeepSeek-R1T-Chimera with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tngtech/DeepSeek-R1T-Chimera" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tngtech/DeepSeek-R1T-Chimera", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tngtech/DeepSeek-R1T-Chimera
- SGLang
How to use tngtech/DeepSeek-R1T-Chimera 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 "tngtech/DeepSeek-R1T-Chimera" \ --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": "tngtech/DeepSeek-R1T-Chimera", "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 "tngtech/DeepSeek-R1T-Chimera" \ --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": "tngtech/DeepSeek-R1T-Chimera", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use tngtech/DeepSeek-R1T-Chimera with Docker Model Runner:
docker model run hf.co/tngtech/DeepSeek-R1T-Chimera
This model is the best for writing, period
I don't know where to write how much I like this model. I tried it on openrouter and it was the best at following complex writing prompts. I'll miss it now that isn't up on openrouter.
For added context I gave the same prompt to every single model on openrouter and this model preformed the best
Thanks for your kind words! The model appears to be still up on the chutes.ai backends and seems to process about 2.5B tokens/day there.
At this moment, we don't know why it isn't up on OpenRouter. The Chimera was processing 900M to 1B tokens/day there during the last week, except when OR had its outages, which affected several models.
Update: It seems to be back and working again at OpenRouter.
It works again! Also, I would be willing to pay tokens for running the model if that means it's more sustainble to have it kept running