Instructions to use MathGPT/DinoSpark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MathGPT/DinoSpark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MathGPT/DinoSpark")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MathGPT/DinoSpark", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MathGPT/DinoSpark with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MathGPT/DinoSpark" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MathGPT/DinoSpark", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MathGPT/DinoSpark
- SGLang
How to use MathGPT/DinoSpark 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 "MathGPT/DinoSpark" \ --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": "MathGPT/DinoSpark", "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 "MathGPT/DinoSpark" \ --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": "MathGPT/DinoSpark", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MathGPT/DinoSpark with Docker Model Runner:
docker model run hf.co/MathGPT/DinoSpark
File size: 891 Bytes
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license: apache-2.0
datasets:
- open-r1/OpenR1-Math-220k
language:
- en
base_model:
- ashabrawy/bert-base-uncased_finetuning_distillation
pipeline_tag: text-generation
metrics:
- accuracy
library_name: transformers
new_version: ashabrawy/bert-base-uncased_finetuning_distillation
tensor_type: F32
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** A team of 2 teenagers
- **Model type:** Text generation
- **Language(s) (NLP):** english
- **License:** apache 2
- **Finetuned from model DeepSeek-R1** |