Instructions to use teddyoas/mathcode-llm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use teddyoas/mathcode-llm with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="teddyoas/mathcode-llm")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("teddyoas/mathcode-llm", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use teddyoas/mathcode-llm with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "teddyoas/mathcode-llm"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "teddyoas/mathcode-llm",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/teddyoas/mathcode-llm

SGLang

How to use teddyoas/mathcode-llm 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 "teddyoas/mathcode-llm" \
    --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": "teddyoas/mathcode-llm",
		"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 "teddyoas/mathcode-llm" \
        --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": "teddyoas/mathcode-llm",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use teddyoas/mathcode-llm with Docker Model Runner:
```
docker model run hf.co/teddyoas/mathcode-llm
```

mathcode-llm

File size: 245 Bytes

2b8a10c

{
  "vocab_size": 32768,
  "n_layer": 12,
  "n_head": 12,
  "n_embd": 768,
  "n_kv_head": 12,
  "block_size": 1024,
  "dropout": 0.0,
  "rope_theta": 10000.0,
  "tie_weights": true,
  "use_swiglu": true,
  "norm_eps": 1e-05,
  "init_std": 0.02
}