Instructions to use NorthernTribe-Research/math-conjecture-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NorthernTribe-Research/math-conjecture-model with Transformers:

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

pipe = pipeline("text-generation", model="NorthernTribe-Research/math-conjecture-model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("NorthernTribe-Research/math-conjecture-model", dtype="auto")

PEFT
How to use NorthernTribe-Research/math-conjecture-model with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use NorthernTribe-Research/math-conjecture-model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NorthernTribe-Research/math-conjecture-model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NorthernTribe-Research/math-conjecture-model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NorthernTribe-Research/math-conjecture-model

SGLang

How to use NorthernTribe-Research/math-conjecture-model 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 "NorthernTribe-Research/math-conjecture-model" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NorthernTribe-Research/math-conjecture-model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "NorthernTribe-Research/math-conjecture-model" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NorthernTribe-Research/math-conjecture-model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use NorthernTribe-Research/math-conjecture-model with Docker Model Runner:
```
docker model run hf.co/NorthernTribe-Research/math-conjecture-model
```

NorthernTribe-Research commited on Mar 25

Commit

95d8f84

verified ·

1 Parent(s): d9dfc8d

Add top-level config.json marker to improve default download-stats counting.

Browse files

Files changed (1) hide show

config.json +16 -0

config.json ADDED Viewed

	@@ -0,0 +1,16 @@

+{
+  "model_type": "peft",
+  "architectures": [
+    "PeftModelForCausalLM"
+  ],
+  "base_model_name_or_path": "Qwen/Qwen2.5-0.5B-Instruct",
+  "peft_type": "LORA",
+  "task_type": "CAUSAL_LM",
+  "_note": "Top-level config.json kept for Hugging Face default download-stats query file counting.",
+  "parameter_counts": {
+    "total_params": 502830976,
+    "trainable_params": 8798208,
+    "frozen_params": 494032768,
+    "trainable_ratio": 0.017497346861940342
+  }
+}