Instructions to use Charley890/AdaptiveMath with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Charley890/AdaptiveMath with Transformers:

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

pipe = pipeline("text-generation", model="Charley890/AdaptiveMath")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Charley890/AdaptiveMath")
model = AutoModelForCausalLM.from_pretrained("Charley890/AdaptiveMath", 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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Charley890/AdaptiveMath with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Charley890/AdaptiveMath"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Charley890/AdaptiveMath",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Charley890/AdaptiveMath

SGLang

How to use Charley890/AdaptiveMath 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 "Charley890/AdaptiveMath" \
    --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": "Charley890/AdaptiveMath",
		"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 "Charley890/AdaptiveMath" \
        --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": "Charley890/AdaptiveMath",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Charley890/AdaptiveMath with Docker Model Runner:
```
docker model run hf.co/Charley890/AdaptiveMath
```

Charley890 commited on 4 days ago

Commit

b7b3005

verified ·

1 Parent(s): 5392fef

Update README.md

Browse files

Files changed (1) hide show

README.md +26 -17

README.md CHANGED Viewed

@@ -217,29 +217,38 @@ A=\pi r^2
 A=49\pi
 ≈153.94
-```
 ```text
-        /|
-       / |
-      /  |
-   c /   | b
-    /    |
-   /_____|
-      a
 ```
 ---
 ```text
-          y
-          ↑
-     4    │        ●
-     3    │
-     2    │
-     1    │
-──────────┼────────────→ x
-    -1    │
-    -2    │
 ```
 ---
 #  Inference with Transformers

 A=49\pi
 ≈153.94
 ```text
+y
+10 |                          ●
+ 9 |                      ●
+ 8 |                  ●
+ 7 |              ●
+ 6 |          ●
+ 5 |      ●
+ 4 |   ●
+ 3 | ●
+   +--------------------------------→ x
+     1   2   3   4   5   6   7   8
 ```
 ---
 ```text
+Frequency
+10 |                    █
+ 9 |                    █
+ 8 |               █    █
+ 7 |               █    █
+ 6 |          █    █    █
+ 5 |     █    █    █    █
+ 4 |     █    █    █    █
+ 3 | █   █    █    █    █
+ 2 | █   █    █    █    █
+ 1 | █   █    █    █    █
+   +----------------------------
+      A    B    C    D    E
 ```
 ---
 #  Inference with Transformers