# Zamba Zamba 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 Zamba-7B-v1 is a hybrid between state-space models (Specifically [Mamba](https://github.com/state-spaces/mamba)) and transformer, and was trained using next-token prediction. Zamba uses a shared transformer layer 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. Zamba-7B-v1 was pre-trained on 1T tokens of text and code data. ## Quick start ### Presequities Zamba requires you use `transformers` version 4.46.0 or higher: ```bash pip install transformers>=4.45.0 ``` In order to run optimized Mamba implementations, you first need to install `mamba-ssm` and `causal-conv1d`: ```bash pip install mamba-ssm causal-conv1d>=1.2.0 ``` You also have to have the model on a CUDA device. You can run the model not using the optimized Mamba kernels, but it is **not** recommended as it will result in significantly lower latencies. In order to do that, you'll need to specify `use_mamba_kernels=False` when loading the model. ## Inference ```python from transformers import AutoTokenizer, AutoModelForCausalLM import torch tokenizer = AutoTokenizer.from_pretrained("Zyphra/Zamba-7B-v1") model = AutoModelForCausalLM.from_pretrained("Zyphra/Zamba-7B-v1", device_map="auto", torch_dtype=torch.bfloat16) input_text = "A funny prompt would be " 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: * [Zamba-7B](MODEL_CARD_ZAMBA-7B-v1.md) ## Issues For issues with model output, or community discussion, please use the Hugging Face community [forum](https://huggingface.co/zyphra/zamba-7b) ## License The model weights are open-sourced via an Apache 2.0 license. ## ZambaConfig [[autodoc]] ZambaConfig ## ZambaModel [[autodoc]] ZambaModel - forward ## ZambaForCausalLM [[autodoc]] ZambaForCausalLM - forward ## ZambaForSequenceClassification [[autodoc]] transformers.ZambaForSequenceClassification - forward