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--- |
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tags: |
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- mamba2 |
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license: mit |
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library_name: transformers |
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--- |
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# mamba2-130m-hf |
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Converted files of the original model at [mamba2-130m](https://huggingface.co/state-spaces/mamba2-130m) to HF transformers compatible formats. |
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Not affiliated with both the original authors or hf. |
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## Usage |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("AntonV/mamba2-130m-hf") |
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model = AutoModelForCausalLM.from_pretrained("AntonV/mamba2-130m-hf") |
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input_ids = tokenizer("Hey how are you doing?", return_tensors="pt")["input_ids"] |
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out = model.generate(input_ids, max_new_tokens=10) |
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print(tokenizer.batch_decode(out)) |
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``` |
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## Citation |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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```bibtex |
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@inproceedings{mamba2, |
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title={Transformers are {SSM}s: Generalized Models and Efficient Algorithms Through Structured State Space Duality}, |
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author={Dao, Tri and Gu, Albert}, |
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booktitle={International Conference on Machine Learning (ICML)}, |
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year={2024} |
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} |
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``` |
