Text Generation
Transformers
PyTorch
reasoning
Android
bilingual
opceanai
termux
flan
fine-tuned
lol
stupid
flan-t5
qDora
Instructions to use OpceanAI/SoTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpceanAI/SoTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpceanAI/SoTa")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpceanAI/SoTa", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use OpceanAI/SoTa with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpceanAI/SoTa" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpceanAI/SoTa", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OpceanAI/SoTa
- SGLang
How to use OpceanAI/SoTa 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 "OpceanAI/SoTa" \ --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": "OpceanAI/SoTa", "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 "OpceanAI/SoTa" \ --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": "OpceanAI/SoTa", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OpceanAI/SoTa with Docker Model Runner:
docker model run hf.co/OpceanAI/SoTa
metadata
license: mit
language:
- es
- en
- fr
- zh
- it
- ru
pipeline_tag: text-generation
library_name: transformers
tags:
- reasoning
- Android
- pytorch
- bilingual
- opceanai
- termux
- flan
- fine-tuned
- lol
- stupid
- flan-t5
- qDora
datasets:
- tsuki-team/Tsuki-dataset
- openlanguagedata/flores_plus
- roneneldan/TinyStories
- wmt/wmt14
- stas/c4-en-10k
- allenai/ai2_arc
- Roman1111111/claude-opus-4.6-10000x
- MaLA-LM/mala-code-reasoning-v3
- theprint/CodeThink-v1-1.04k
- Jackrong/DeepSeek-V4-Distill-8000x
- sequelbox/Titanium2.1-DeepSeek-R1
- RUC-AIBOX/STILL-3-Preview-RL-Data
- ai4privacy/pii-masking-300k
- jinulee-v/omnimath
- open-r1/OpenR1-Math-220k
- PJMixers-Dev/nvidia-r1-code-1k-think-256-response-filtered-ShareGPT
- trjxter/Kimi-K2.6-Reasoning-3300x-WandB
- allenai/Dolci-Think-SFT-32B
- OpceanAI/sota-hard
- OpceanAI/sota-general
- OpceanAI/sota-math