Instructions to use pmahdavi/Olmo-3-7B-Think-Math-Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pmahdavi/Olmo-3-7B-Think-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-Think-Math-Code")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("pmahdavi/Olmo-3-7B-Think-Math-Code") model = AutoModelForCausalLM.from_pretrained("pmahdavi/Olmo-3-7B-Think-Math-Code", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pmahdavi/Olmo-3-7B-Think-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-Think-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-Think-Math-Code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pmahdavi/Olmo-3-7B-Think-Math-Code
- SGLang
How to use pmahdavi/Olmo-3-7B-Think-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-Think-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-Think-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-Think-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-Think-Math-Code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pmahdavi/Olmo-3-7B-Think-Math-Code with Docker Model Runner:
docker model run hf.co/pmahdavi/Olmo-3-7B-Think-Math-Code
File size: 1,746 Bytes
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base_model:
- allenai/Olmo-3-1025-7B
- allenai/Olmo-3-7B-RL-Zero-Math
- allenai/Olmo-3-7B-RL-Zero-Code
- allenai/Olmo-3-7B-Think-SFT
library_name: transformers
tags:
- mergekit
- merge
---
# merged-model
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Task Arithmetic](https://arxiv.org/abs/2212.04089) merge method using [allenai/Olmo-3-1025-7B](https://huggingface.co/allenai/Olmo-3-1025-7B) as a base.
### Models Merged
The following models were included in the merge:
* [allenai/Olmo-3-7B-RL-Zero-Math](https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Math)
* [allenai/Olmo-3-7B-RL-Zero-Code](https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Code)
* [allenai/Olmo-3-7B-Think-SFT](https://huggingface.co/allenai/Olmo-3-7B-Think-SFT)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
# Task arithmetic merge: Apply Math+Code task vectors to Think-SFT
#
# Mathematical formulation:
# output = Think-SFT + 0.5*(RL-Zero-Math - base) + 0.5*(RL-Zero-Code - base)
#
# This is achieved by treating Think-SFT as a model with weight=1.0:
# output = base + 1.0*(Think-SFT - base) + 0.5*(Math - base) + 0.5*(Code - base)
#
# Usage:
# modal run modal_merge.py --config examples/olmo-think-math-code.yaml --hf-repo pmahdavi/Olmo-3-7B-Think-Math-Code
merge_method: task_arithmetic
base_model: allenai/Olmo-3-1025-7B
models:
- model: allenai/Olmo-3-7B-Think-SFT
parameters:
weight: 1.0
- model: allenai/Olmo-3-7B-RL-Zero-Math
parameters:
weight: 0.5
- model: allenai/Olmo-3-7B-RL-Zero-Code
parameters:
weight: 0.5
dtype: bfloat16
```
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