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@@ -8,18 +8,18 @@ license: mit
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  ---
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  # babybabellm-multismall
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- This repository contains checkpoints for the **multismall** variant of **BabyBabeLLM**.
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  ## Files
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  - `*_15_16.bin` – main model weights
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  - `*_15_16_ema.bin` – EMA smoothed weights
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  - `*_15_16_state_dict.bin` – PyTorch state dict
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  - `pytorch_model.bin` – extracted EMA weights (for AutoModel)
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- - Config + tokenizer files for model loading (zipped in shared_files.zip)
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  ## Usage
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  ```python
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  from transformers import AutoModel, AutoTokenizer
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- repo = "suchirsalhan/babybabellm-multismall"
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  tokenizer = AutoTokenizer.from_pretrained(repo)
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  model = AutoModel.from_pretrained(repo)
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  inputs = tokenizer("Hello world!", return_tensors="pt")
@@ -27,5 +27,5 @@ outputs = model(**inputs)
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  ```
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  ## Notes
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  - These are research checkpoints trained on BabyLM-style data.
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- - Model naming: `multismall` indicates the language/config variant.
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  ---
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  # babybabellm-multismall
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+ This repository contains checkpoints for the **multilingual (all)** variant of **BabyBabeLLM**.
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  ## Files
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  - `*_15_16.bin` – main model weights
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  - `*_15_16_ema.bin` – EMA smoothed weights
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  - `*_15_16_state_dict.bin` – PyTorch state dict
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  - `pytorch_model.bin` – extracted EMA weights (for AutoModel)
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+
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  ## Usage
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  ```python
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  from transformers import AutoModel, AutoTokenizer
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+ repo = "suchirsalhan/babybabellm-multi-all"
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  tokenizer = AutoTokenizer.from_pretrained(repo)
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  model = AutoModel.from_pretrained(repo)
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  inputs = tokenizer("Hello world!", return_tensors="pt")
 
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  ```
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  ## Notes
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  - These are research checkpoints trained on BabyLM-style data.
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+ - Model naming: `multiall` indicates the language/config variant.
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