Instructions to use pmahdavi/Olmo-3-7B-RL-Zero-Math-Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pmahdavi/Olmo-3-7B-RL-Zero-Math-Code with Transformers:

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

pipe = pipeline("text-generation", model="pmahdavi/Olmo-3-7B-RL-Zero-Math-Code")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pmahdavi/Olmo-3-7B-RL-Zero-Math-Code")
model = AutoModelForCausalLM.from_pretrained("pmahdavi/Olmo-3-7B-RL-Zero-Math-Code")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use pmahdavi/Olmo-3-7B-RL-Zero-Math-Code with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pmahdavi/Olmo-3-7B-RL-Zero-Math-Code"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pmahdavi/Olmo-3-7B-RL-Zero-Math-Code",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/pmahdavi/Olmo-3-7B-RL-Zero-Math-Code

SGLang

How to use pmahdavi/Olmo-3-7B-RL-Zero-Math-Code 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 "pmahdavi/Olmo-3-7B-RL-Zero-Math-Code" \
    --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": "pmahdavi/Olmo-3-7B-RL-Zero-Math-Code",
		"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 "pmahdavi/Olmo-3-7B-RL-Zero-Math-Code" \
        --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": "pmahdavi/Olmo-3-7B-RL-Zero-Math-Code",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use pmahdavi/Olmo-3-7B-RL-Zero-Math-Code with Docker Model Runner:
```
docker model run hf.co/pmahdavi/Olmo-3-7B-RL-Zero-Math-Code
```

pmahdavi commited on Jan 9

Commit

3816165

verified ·

1 Parent(s): be1faed

Delete chat_template.jinja

Browse files

Files changed (1) hide show

chat_template.jinja +0 -16

chat_template.jinja DELETED Viewed

@@ -1,16 +0,0 @@
-{% set has_system = messages|selectattr('role', 'equalto', 'system')|list|length > 0 %}{% if not has_system %}{{ '<|im_start|>system
-You are OLMo, a helpful function-calling AI assistant built by Ai2. Your date cutoff is November 2024, and your model weights are available at https://huggingface.co/allenai. You do not currently have access to any functions. <functions></functions><|im_end|>
-' }}{% endif %}{% for message in messages %}{% if message['role'] == 'system' %}{{ '<|im_start|>system
-' + message['content'] }}{% if message.get('functions', none) is not none %}{{ ' <functions>' + message['functions'] + '</functions><|im_end|>
-' }}{% else %}{{ ' You do not currently have access to any functions. <functions></functions><|im_end|>
-' }}{% endif %}{% elif message['role'] == 'user' %}{% if message.get('functions', none) is not none %}{{ '<|im_start|>user
-' + message['content'] + '
-' + '<functions>' + message['functions'] + '</functions><|im_end|>
-' }}{% else %}{{ '<|im_start|>user
-' + message['content'] + '<|im_end|>
-' }}{% endif %}{% elif message['role'] == 'assistant' %}{{ '<|im_start|>assistant
-' }}{% if message.get('content', none) is not none %}{{ message['content'] }}{% endif %}{% if message.get('function_calls', none) is not none %}{{ '<function_calls>' + message['function_calls'] + '</function_calls>' }}{% endif %}{% if not loop.last %}{{ '<|im_end|>' + '
-' }}{% else %}{{ eos_token }}{% endif %}{% elif message['role'] == 'environment' %}{{ '<|im_start|>environment
-' + message['content'] + '<|im_end|>
-' }}{% endif %}{% if loop.last and add_generation_prompt %}{{ '<|im_start|>assistant
-<think>' }}{% endif %}{% endfor %}