Olmo-3-Think

About

What Olmo-3-Think is

Model Details Model Card for Olmo 3 Think We introduce Olmo 3, a new family of 7B and 32B models both Instruct and Think variants. Long chain-of-thought thinking improves reasoning tasks like math and coding. Olmo is a series of Open language models designed to enable the science of language models. These models are pre-trained on the Dolma 3 dataset and post-trained on the Dolci datasets. We are releasing all code, checkpoints, logs (coming soon), and associated training details. The core models released in this batch include the following: Installation Olmo 3 is supported in transformers 4.57.0 or higher: Inference You can use OLMo with the standard HuggingFace transformers library: For faster performance, you can quantize the model using the following method: The quantized model is more sensitive to data types and CUDA operations. To avoid potential issues, it's recommended to pass the inputs directly to CUDA using: We have released checkpoints for these models. For post-training, the naming convention is stepXXXX. To load a specific model revision with HuggingFace, simply add the argument revision: Or, you can access all the revisions for the models via the following code snippet: Chat template Default System Message The default system prompt for this model is: Chat Format The chat template for this model is formatted as: Model Description - Developed by: Allen Institute for AI (Ai2) - Model type: a Transformer style autoregressive language model. - Language(s) (NLP): English - License: This model is licensed under Apache 2.0. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines. - Contact: Technical inquiries: olmo@allenai.org. Press: press@allenai.org - Date cutoff: Dec. 2024. Model Sources - Project Page: https://allenai.org/olmo - Repositories: - Open-Instruct for DPO and RLVR: https://github.com/allenai/open-instruct - OLMo-Core for pre-training and SFT: https://github.com/allenai/OLMo-core - OLMo-Eval for evaluation: https://github.com/allenai/OLMo-Eval - Paper: [TBD] Evaluation Model Details Stage 1: SFT - supervised fine-tuning on the Dolci-Think-SFT-7B dataset. This dataset consits of math, code, chat,

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys olmo-3-think for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (olmo-3-think below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"olmo-3-think","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Papers

Licence

Open weights

Sources

Weights & code

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