Instructions to use Jeremmmyyyyy/math-no-normalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Jeremmmyyyyy/math-no-normalization with Transformers:

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

pipe = pipeline("text-generation", model="Jeremmmyyyyy/math-no-normalization")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Jeremmmyyyyy/math-no-normalization")
model = AutoModelForCausalLM.from_pretrained("Jeremmmyyyyy/math-no-normalization", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Jeremmmyyyyy/math-no-normalization with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Jeremmmyyyyy/math-no-normalization"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Jeremmmyyyyy/math-no-normalization",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Jeremmmyyyyy/math-no-normalization

SGLang

How to use Jeremmmyyyyy/math-no-normalization 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 "Jeremmmyyyyy/math-no-normalization" \
    --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": "Jeremmmyyyyy/math-no-normalization",
		"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 "Jeremmmyyyyy/math-no-normalization" \
        --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": "Jeremmmyyyyy/math-no-normalization",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Jeremmmyyyyy/math-no-normalization with Docker Model Runner:
```
docker model run hf.co/Jeremmmyyyyy/math-no-normalization
```

Jeremmmyyyyy commited on May 14, 2025

Commit

1eb4748

verified ·

1 Parent(s): 60fee1f

Training in progress, step 150

Browse files

Files changed (2) hide show

model.safetensors +1 -1
runs/May14_16-15-15_kl002/events.out.tfevents.1747232142.kl002 +2 -2

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2774399d92ede0024ad826501362114e35de5b29b135e1e2cb7d3eb3fc0c3038
 size 1999811208

 version https://git-lfs.github.com/spec/v1
+oid sha256:ef7561ef7b9fb4fe16b57ca411bdf2b84e32856699370151e376add74f10ce11
 size 1999811208

runs/May14_16-15-15_kl002/events.out.tfevents.1747232142.kl002 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d3a8249c1922462bc1cbf5619a33759d628bce56dc4443e8d94fb0309c8774c1
-size 197249

 version https://git-lfs.github.com/spec/v1
+oid sha256:1630f0f2dd5388295362a1e67dc1bf3434bc6cf1cfca19b6437b64adb9ae2e5a
+size 235990