allenai/OLMo-2-0425-1B
text-generation model by allenai
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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: 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 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…
Read the full model card ↗ · Preview checked 2026-10-30T19:41:08.825Z
Inside the original model card — Document outline
- Model Details
- Model Card for OLMo 2 1B
- Installation
- Inference
- Fine-tuning
- Model Description
- Model Sources
- Evaluation
- Model Details
- Training
- Stage 1: Initial Pretraining
- Stage 2: Mid-training
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Model overview
allenai/OLMo-2-0425-1B is a text-generation model repository published by allenai on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- transformers
- Recent downloads (30 days)
- 919,400
- Cumulative likes
- 81
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 1,484,916,736
- Architecture
- Olmo2ForCausalLM
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2025-04-17T22:45:45.000Z
- Last modified
- 2025-05-28T20:35:45.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-15T06:34:04.087Z. Daily imports are snapshots, not real-time monitoring.
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