README.md

---
license: mit
language:
- en
---

# Mamba

<!-- Provide a quick summary of what the model is/does. -->
This repository contains the `transfromers` compatible `mamba-2.8b`. The checkpoints are untouched, but the full `config.json` and tokenizer are pushed to this repo. 

# Usage

You need to install `transformers` from `main` until `transformers=4.39.0` is released. 
```bash
pip install git+https://github.com/huggingface/transformers@main
```

We also recommend you to install both `causal_conv_1d` and `mamba-ssm` using: 

```bash
pip install causal-conv1d>=1.2.0
pip install mamba-ssm
```

If any of these two is not installed, the "eager" implementation will be used. Otherwise the more optimised `cuda` kernels will be used.

## Generation
You can use the classic `generate` API:
```python
>>> from transformers import MambaConfig, MambaForCausalLM, AutoTokenizer
>>> import torch

>>> tokenizer = AutoTokenizer.from_pretrained("state-spaces/mamba-790m-hf")
>>> model = MambaForCausalLM.from_pretrained("state-spaces/mamba-790m-hf")
>>> input_ids = tokenizer("Hey how are you doing?", return_tensors="pt")["input_ids"]

>>> out = model.generate(input_ids, max_new_tokens=10)
>>> print(tokenizer.batch_decode(out))
["Hey how are you doing?\n\nI'm good.\n\nHow are"]
```