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            ### Intended use
         
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            This model was trained on English math data and is not instruction-tuned, making it intended for text completion in English.
         
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            ### Generation
         
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            print(tokenizer.decode(outputs[0]))
         
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            ```
         
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            ## Intermediate checkpoints 
         
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            We are releasing intermediate checkpoints for this model at intervals of every 10000 training steps (10B tokens) in separate branches. The naming convention is `10B`.
         
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            You can load a specific model revision with `transformers` using the argument `revision`:
         
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            ```python
         
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            model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/FineMath-Llama-3B", revision="10B")
         
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            ```
         
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            You can access all the revisions for the models via the following code:
         
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            ```python
         
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            from huggingface_hub import list_repo_refs
         
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            out = list_repo_refs("HuggingFaceTB/FineMath-Llama-3B")
         
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            print([b.name for b in out.branches])
         
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            ```
         
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            ## Training
         
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            ### Model
         
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            - **Architecture**: Llama3  
         
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            ### Intended use
         
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            This model was trained on English math data and is not instruction-tuned, making it intended for text completion in English. It is part of the FineMath ablation models we trained for FineMath (https://huggingface.co/HuggingFaceTB/finemath-ablation-4plus-160B), and is not necessarily the best possible outcome achievable with the given dataset.
         
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            ### Generation
         
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            print(tokenizer.decode(outputs[0]))
         
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            ```
         
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            ## Training
         
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            ### Model
         
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            - **Architecture**: Llama3  
         
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