Olmo-3-1125

About

What Olmo-3-1125 is

Model Details Model Card for Olmo 3 32B We introduce Olmo 3, a new family of 7B and 32B models. This suite includes Base, Instruct, and Think variants. The Base models were trained using a staged training approach. Olmo is a series of Open language models designed to enable the science of language models. These models are trained on the Dolma 3 dataset. We are releasing all code, checkpoints, and associated training details. The core models released in this batch include the following: Installation Olmo 3 is supported in transformers v4.57.0 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 pretraining, the naming convention is stage1-stepXXX. The conventions for midtraining and long context are stage2-ingredientY-stepXXX and stage3-stepXXX, respectively. 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: Fine-tuning Model fine-tuning can be done from the final checkpoint (the main revision of this model) or many intermediate checkpoints. Two recipes for tuning are available. 1. Fine-tune with the OLMo-core repository: You can override most configuration options from the command-line. For example, to override the learning rate you could launch the script like this: For more documentation, see the GitHub readme. Model Description - Developed by: Allen Institute for AI (Ai2) - Model type: a Transformer style autoregressive language model. - Language(s) (NLP): English - License: The code and model are released under Apache 2.0. - Contact: Technical inquiries: olmo@allenai.org. Press: press@allenai.org - Date cutoff: Dec 2024 Model Sources - Project Page: https://allenai.org/olmo - Repositories: - Core repo (training, inference, fine-tuning etc.): https://github.com/allenai/OLMo-core - Evaluation code: https://github.com/alle

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.

Benchmarks

Reported results

As published on the model card — the maker's own numbers, not measured by AxForge.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys olmo-3-1125 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (olmo-3-1125 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-3-1125","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Licence

Open weights

Sources

Weights & code

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