# Zamba2
Zamba2 is a large language model (LLM) trained by Zyphra, and made available under an Apache 2.0 license. Please see the [Zyphra Hugging Face](https://huggingface.co/collections/zyphra/) repository for model weights.
This model was contributed by [pglo](https://huggingface.co/pglo).
## Model details
Zamba2-1.2B, Zamba2-2.7B and Zamba2-7B are hybrid models combining state-space models (Specifically [Mamba](https://github.com/state-spaces/mamba)) and transformer, and were trained using next-token prediction. Zamba2 uses shared transformer layers after every 6 mamba blocks. It uses the [Mistral v0.1 tokenizer](https://huggingface.co/mistralai/Mistral-7B-v0.1). We came to this architecture after a series of ablations at small scales. Zamba2-1.2B, Zamba2-2.7B and Zamba2-7B were pre-trained on 2T and 3T tokens, respectively.
## Quick start
### Presequities
Zamba2 requires you use `transformers` version 4.48.0 or higher:
```bash
pip install transformers>=4.48.0
```
## Inference
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("Zyphra/Zamba2-7B")
model = AutoModelForCausalLM.from_pretrained("Zyphra/Zamba2-7B", device_map="cuda", torch_dtype=torch.bfloat16)
input_text = "What factors contributed to the fall of the Roman Empire?"
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**input_ids, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))
```
## Model card
The model cards can be found at:
* [Zamba2-1.2B](https://huggingface.co/Zyphra/Zamba2-1.2B)
* [Zamba2-2.7B](https://huggingface.co/Zyphra/Zamba2-2.7B)
* [Zamba2-7B](https://huggingface.co/Zyphra/Zamba2-7B)
## Issues
For issues with model output, or community discussion, please use the Hugging Face community [forum](https://huggingface.co/Zyphra/Zamba2-7B/discussions)
## License
The model weights are open-sourced via an Apache 2.0 license.
## Zamba2Config
[[autodoc]] Zamba2Config
## Zamba2Model
[[autodoc]] Zamba2Model
- forward
## Zamba2ForCausalLM
[[autodoc]] Zamba2ForCausalLM
- forward
## Zamba2ForSequenceClassification
[[autodoc]] transformers.Zamba2ForSequenceClassification
- forward
