Text Generation
Transformers
Safetensors
triangulum_10b
sft
chain_of_thought
ollama
text-generation-inference
llama_for_causal_lm
reasoning
CoT
Instructions to use prithivMLmods/Triangulum-10B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Triangulum-10B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="prithivMLmods/Triangulum-10B")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prithivMLmods/Triangulum-10B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use prithivMLmods/Triangulum-10B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "prithivMLmods/Triangulum-10B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Triangulum-10B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/prithivMLmods/Triangulum-10B
- SGLang
How to use prithivMLmods/Triangulum-10B 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 "prithivMLmods/Triangulum-10B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Triangulum-10B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "prithivMLmods/Triangulum-10B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prithivMLmods/Triangulum-10B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use prithivMLmods/Triangulum-10B with Docker Model Runner:
docker model run hf.co/prithivMLmods/Triangulum-10B
| { | |
| "additional_special_tokens": [ | |
| ">>TITLE<<", | |
| ">>ABSTRACT<<", | |
| ">>INTRODUCTION<<", | |
| ">>SUMMARY<<", | |
| ">>COMMENT<<", | |
| ">>ANSWER<<", | |
| ">>QUESTION<<", | |
| ">>DOMAIN<<", | |
| ">>EMAIL_ADDRESS<<", | |
| ">>IP_ADDRESS<<", | |
| "<|startoftext|>", | |
| ">>IP_ADDRESS_0<<", | |
| ">>IP_ADDRESS_1<<", | |
| ">>IP_ADDRESS_2<<", | |
| ">>IP_ADDRESS_3<<", | |
| ">>IP_ADDRESS_4<<", | |
| ">>IP_ADDRESS_5<<", | |
| ">>IP_ADDRESS_6<<", | |
| ">>IP_ADDRESS_7<<", | |
| ">>IP_ADDRESS_8<<", | |
| ">>IP_ADDRESS_9<<", | |
| ">>PASSWORD<<", | |
| ">>KEY<<" | |
| ], | |
| "eos_token": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "<|pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |