Instructions to use leeroo/LeerooDedicated-Math-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use leeroo/LeerooDedicated-Math-7b with Transformers:

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

pipe = pipeline("text-generation", model="leeroo/LeerooDedicated-Math-7b", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("leeroo/LeerooDedicated-Math-7b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("leeroo/LeerooDedicated-Math-7b", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use leeroo/LeerooDedicated-Math-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "leeroo/LeerooDedicated-Math-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "leeroo/LeerooDedicated-Math-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/leeroo/LeerooDedicated-Math-7b

SGLang

How to use leeroo/LeerooDedicated-Math-7b 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 "leeroo/LeerooDedicated-Math-7b" \
    --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": "leeroo/LeerooDedicated-Math-7b",
		"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 "leeroo/LeerooDedicated-Math-7b" \
        --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": "leeroo/LeerooDedicated-Math-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use leeroo/LeerooDedicated-Math-7b with Docker Model Runner:
```
docker model run hf.co/leeroo/LeerooDedicated-Math-7b
```

alirezamsh commited on Apr 2, 2024

Commit

54186ce

verified ·

1 Parent(s): 4bab141

Update README.md

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -30,7 +30,7 @@ generated_ids = model.generate(model_inputs, max_new_tokens=100, do_sample=False
 decoded = tokenizer.batch_decode(generated_ids)
 print(decoded[0])
 # Natalia sold 48 clips in April.\nIn May, she sold half as many clips as in April,
-# so she sold 48/2 = 24 clips.\nAltogether, Natalia sold 48 + 24 = 72 clips in April and May.\n#### 72\nThe answer is: 72</s>'
 # sends the following questin to GPT4
 question = "James loves to go swimming and has to swim across a 20-mile lake.  He can swim at a pace of 2 miles per hour.  He swims 60% of the distance.  After that, he stops on an island and rests for half as long as the swimming time.  He then finishes the remaining distance while going half the speed.  How long did it take him to get across the lake?"
@@ -39,7 +39,7 @@ model_inputs = encodeds['input_ids'].to(device)
 generated_ids = model.generate(model_inputs, max_new_tokens=100, do_sample=False)
 decoded = tokenizer.batch_decode(generated_ids)
 print(decoded[0])
-# <GPT4></s>'
 ```
 ## Learn More

 decoded = tokenizer.batch_decode(generated_ids)
 print(decoded[0])
 # Natalia sold 48 clips in April.\nIn May, she sold half as many clips as in April,
+# so she sold 48/2 = 24 clips.\nAltogether, Natalia sold 48 + 24 = 72 clips in April and May.\n#### 72\nThe answer is: 72</s>
 # sends the following questin to GPT4
 question = "James loves to go swimming and has to swim across a 20-mile lake.  He can swim at a pace of 2 miles per hour.  He swims 60% of the distance.  After that, he stops on an island and rests for half as long as the swimming time.  He then finishes the remaining distance while going half the speed.  How long did it take him to get across the lake?"
 generated_ids = model.generate(model_inputs, max_new_tokens=100, do_sample=False)
 decoded = tokenizer.batch_decode(generated_ids)
 print(decoded[0])
+# <GPT4></s>
 ```
 ## Learn More