| ---
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| language:
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| - en
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| license: apache-2.0
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| library_name: transformers
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| pipeline_tag: text-generation
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| tags:
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| - mamba
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| - state-space-model
|
| - ssm
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| - causal-lm
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| - pytorch
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| - pretrained
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| datasets:
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| - wikimedia/wikipedia
|
| ---
|
|
|
| # Mamba-50M
|
|
|
| A ~50M-parameter [Mamba](https://arxiv.org/abs/2312.00752) (selective state-space) causal
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| language model, **pretrained from scratch on English Wikipedia**. Mamba replaces the attention
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| mechanism of a Transformer with a selective state-space layer, giving linear-time sequence
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| processing instead of the quadratic cost of self-attention.
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|
|
| > **This is a base model: pretrained only.** It has **not** been fine-tuned, instruction-tuned,
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| > RLHF'd, or aligned in any way. It is a raw next-token predictor intended for research.
|
|
|
| ## Model details
|
|
|
| | | |
|
| |---|---|
|
| | Architecture | Mamba (selective SSM) |
|
| | Parameters | ~50M |
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| | Context length | 512 tokens |
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| | Tokenizer | [GPT-NeoX-20B](https://huggingface.co/EleutherAI/gpt-neox-20b) (BPE, ~50k vocab) — the same tokenizer used by the original `state-spaces/mamba-*` models |
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| | Language | English |
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| | License | Apache-2.0 |
|
|
|
| ## Limitations
|
|
|
| - **Pretrained only.** No fine-tuning, instruction tuning, or alignment. It does not follow instructions and has no safety filtering; it simply continues text.
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| - **Small.** At ~50M parameters it has limited fluency and reasoning; expect frequent hallucination and repetition.
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| - **English only.** Trained solely on English Wikipedia; other languages are out of distribution.
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| - **Domain-narrow.** Only Wikipedia was used as training data.
|
|
|
| ## Training data
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|
|
| Pretrained on the English subset of Wikipedia: over 3 million articles.
|
|
|
| ### Training procedure
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|
|
| | Hyperparameter | Value |
|
| |---|---|
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| | Learning rate | 5e-4 |
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| | Sequence length | 512 |
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| | Batch size | 64 |
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| | Tokenizer | GPT-NeoX-20B (`EleutherAI/gpt-neox-20b`) |
|
| | Optimizer | `AdamW` |
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| | LR schedule / warmup | `constant` / `10000` |
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| | Total tokens seen | `~ 2.5-2.9B` |
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| | Hardware | `2x Nvidia Quadro RTX 6000 24GB` |
|
|
|
| ## Evaluation
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|
|
| Evaluated on a held-out set of **10,000 Wikipedia articles** that were not seen during training.
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| The training and evaluation loss curves are shown below.
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|
|
| 
|
|
|
| ## Citation
|
|
|
| If you use this model, please cite the Mamba paper:
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|
|
| ```bibtex
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| @article{gu2023mamba,
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| title={Mamba: Linear-Time Sequence Modeling with Selective State Spaces},
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| author={Gu, Albert and Dao, Tri},
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| journal={arXiv preprint arXiv:2312.00752},
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| year={2023}
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| }
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| ```
|
|
|
