OLMo-2-0425

About

What OLMo-2-0425 is

Model Details Model Card for OLMo 2 1B We introduce OLMo 2 1B, the smallest model in the OLMo 2 family. OLMo 2 was pre-trained on OLMo-mix-1124 and uses Dolmino-mix-1124 for mid-training. OLMo 2 is the latest in a series of Open Language Models designed to enable the science of language models. We have released all code, checkpoints, logs, and associated training details on GitHub. The core models released in this batch include the following: Installation OLMo 2 1B is supported in transformers v4.48 or higher: If using vLLM, you will need to install from the main branch until v0.7.4 is released. Please 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-tokensYYYB. For checkpoints with ingredients of the soup, the naming convention is stage2-ingredientN-stepXXX-tokensYYYB 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 repository: For more documentation, see the GitHub README. 2. Further fine-tuning support is being developing in AI2's Open Instruct repository. Details are here. 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. 2023. Model Sources - Project Page: https://allenai.org/olmo - Repositories: - Core repo (training, inference, fine-tuning etc.): https://github.com/allenai/OLMo - Evaluation code: https://github.com/

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-2-0425 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (olmo-2-0425 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-2-0425","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Papers

Licence

Open weights

Sources

Weights & code

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