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README.md
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<img src="https://allenai.org/olmo/olmo-7b-animation.gif" alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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# Model Card for OLMo
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**Requires transformers versions v4.40.0 or newer**
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The OLMo base models are trained on the [Dolma](https://huggingface.co/datasets/allenai/dolma) dataset.
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The adapted versions are trained on the [Tulu SFT mixture](https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture) and, for the Instruct version, a [cleaned version of the UltraFeedback dataset](https://huggingface.co/datasets/allenai/ultrafeedback_binarized_cleaned).
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OLMo
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They show the performance gain that OLMo base models can achieve with existing fine-tuning techniques.
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## Model Details
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We release two adapted model versions:
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| Model | Training Method(s) | Datasets | Context Length |
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|------|--------|---------|--|
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| [OLMo
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| [OLMo
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These models are both trained on top of OLMo
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| Size | Training Tokens | Layers | Hidden Size | Attention Heads | Context Length |
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|------|--------|---------|-------------|-----------------|----------------|
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| [OLMo
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### Model Description
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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olmo = AutoModelForCausalLM.from_pretrained("allenai/OLMo-
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tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-
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chat = [
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{ "role": "user", "content": "What is language modeling?" },
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]
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| Model | MMLU 0-shot β | AlpacaEval %win β | ToxiGen % Toxic β | TruthfulQA %Info+True β |
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|-----------------------|---------------|--------------------|--------------------|-------------------------|
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| **OLMo
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| **[OLMo
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| **[OLMo
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<img src="https://allenai.org/olmo/olmo-7b-animation.gif" alt="OLMo Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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# Model Card for OLMo 7B July 2024 Instruct
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**Requires transformers versions v4.40.0 or newer**
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The OLMo base models are trained on the [Dolma](https://huggingface.co/datasets/allenai/dolma) dataset.
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The adapted versions are trained on the [Tulu SFT mixture](https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture) and, for the Instruct version, a [cleaned version of the UltraFeedback dataset](https://huggingface.co/datasets/allenai/ultrafeedback_binarized_cleaned).
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OLMo 7B Instruct SFT are two adapted versions of these models trained for better question answering.
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These are updated OLMo models corresponding to our July 2024 release.
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They show the performance gain that OLMo base models can achieve with existing fine-tuning techniques.
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## Model Details
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We release two adapted model versions:
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| Model | Training Method(s) | Datasets | Context Length |
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|------|--------|---------|--|
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| [OLMo 7B July 2024 SFT](https://huggingface.co/allenai/OLMo-1.7-7B-Nitro-SFT-hf) | SFT | [Tulu 2 SFT Mix](https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture) | 2048 |
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| [OLMo 7B July 2024 Instruct](https://huggingface.co/allenai/OLMo-1.7-7B-Nitro-Instruct-hf) | SFT + DPO | [Tulu 2 SFT Mix](https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture) + [Ultrafeedback Cleaned](https://huggingface.co/datasets/allenai/ultrafeedback_binarized_cleaned) | 2048 |
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These models are both trained on top of OLMo 7b July 2024:
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| Size | Training Tokens | Layers | Hidden Size | Attention Heads | Context Length |
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|------|--------|---------|-------------|-----------------|----------------|
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| [OLMo 7B July 2024](https://huggingface.co/allenai/OLMo-1.7-7B-hf) | 2.7T |32 | 4096 | 32 | 4096 |
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### Model Description
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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olmo = AutoModelForCausalLM.from_pretrained("allenai/OLMo-7B-0724-Instruct-hf")
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tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-7B-0724-Instruct-hf")
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chat = [
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{ "role": "user", "content": "What is language modeling?" },
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]
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| Model | MMLU 0-shot β | AlpacaEval %win β | ToxiGen % Toxic β | TruthfulQA %Info+True β |
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|-----------------------|---------------|--------------------|--------------------|-------------------------|
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| **OLMo July 2024 base** | 50.8 | - | 85.2 | 28.4 |
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| **[OLMo 7B July 2024 SFT](https://huggingface.co/allenai/OLMo-1.7-7B-Nitro-SFT-hf)** | 54.2 | 70.9 | .1 | 44.4 |
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| **[OLMo 7B July 2024 Instruct](https://huggingface.co/allenai/OLMo-1.7-7B-Nitro-Instruct-hf)** | 52.8 | 83.5 | 1.7 | 70.3 |
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