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")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MathGPT/DinoSpark", dtype="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
Update README.md
Browse files
README.md
CHANGED
|
@@ -26,10 +26,8 @@ This modelcard aims to be a base template for new models. It has been generated
|
|
| 26 |
|
| 27 |
|
| 28 |
|
| 29 |
-
- **Developed by:**
|
| 30 |
-
- **
|
| 31 |
-
- **
|
| 32 |
-
- **
|
| 33 |
-
- **
|
| 34 |
-
- **License:** [apache 2]
|
| 35 |
-
- **Finetuned from model [DeepSeek-R1]:** [More Information Needed]
|
|
|
|
| 26 |
|
| 27 |
|
| 28 |
|
| 29 |
+
- **Developed by:** A team of 2 teenagers
|
| 30 |
+
- **Model type:** Text generation
|
| 31 |
+
- **Language(s) (NLP):** english
|
| 32 |
+
- **License:** apache 2
|
| 33 |
+
- **Finetuned from model DeepSeek-R1**
|
|
|
|
|
|