Text Generation
Transformers
PyTorch
English
hf_olmo
conversational
custom_code
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@@ -15,6 +15,8 @@ language:
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  <!-- Provide a quick summary of what the model is/does. -->
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  OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the science of language models.
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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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  ```
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  Now, proceed as usual with HuggingFace:
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  ```python
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- import hf_olmo
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-
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- from transformers import AutoModelForCausalLM, AutoTokenizer
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- olmo = AutoModelForCausalLM.from_pretrained("allenai/OLMo-7B-SFT")
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- tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-7B-SFT")
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  chat = [
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  { "role": "user", "content": "What is language modeling?" },
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  ]
 
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  <!-- Provide a quick summary of what the model is/does. -->
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+ **For transformers versions v4.40.0 or newer, we suggest using [OLMo 7B SFT HF](https://huggingface.co/allenai/OLMo-7B-SFT-hf) instead.**
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+
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  OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the science of language models.
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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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  ```
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  Now, proceed as usual with HuggingFace:
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  ```python
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+ from hf_olmo import OLMoForCausalLM, OLMoTokenizerFast
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+ olmo = OLMoForCausalLM.from_pretrained("allenai/OLMo-7B-SFT")
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+ tokenizer = OLMoTokenizerFast.from_pretrained("allenai/OLMo-7B-SFT")
 
 
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  chat = [
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  { "role": "user", "content": "What is language modeling?" },
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  ]