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---
license: wtfpl
datasets:
- HuggingFaceH4/no_robots
pipeline_tag: text-generation
---
# MAMBA (2.8B) 🐍 fine-tuned on OpenHerms
Model Card is still WIP!
## Base model info
Mamba is a new state space model architecture showing promising performance on information-dense data such as language modeling, where previous subquadratic models fall short of Transformers.
It is based on the line of progress on [structured state space models](https://github.com/state-spaces/s4),
with an efficient hardware-aware design and implementation in the spirit of [FlashAttention](https://github.com/Dao-AILab/flash-attention).
## Dataset info
TBA
## Usage
```sh
pip install transformers
pip install causal-conv1d<=1.0.2
pip install mamba-ssm
```
```py
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
from mamba_ssm.models.mixer_seq_simple import MambaLMHeadModel
CHAT_TEMPLATE_ID = "HuggingFaceH4/zephyr-7b-beta"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model_name = "clibrain/mamba-2.8b-instruct-openhermes"
eos_token = "<|endoftext|>"
tokenizer = AutoTokenizer.from_pretrained(model_name)
tokenizer.eos_token = eos_token
tokenizer.pad_token = tokenizer.eos_token
tokenizer.chat_template = AutoTokenizer.from_pretrained(CHAT_TEMPLATE_ID).chat_template
model = MambaLMHeadModel.from_pretrained(
model_name, device=device, dtype=torch.float16)
history_dict: list[dict[str, str]] = []
prompt = "Tell me 5 sites to visit in Spain"
history_dict.append(dict(role="user", content=prompt))
input_ids = tokenizer.apply_chat_template(
history_dict, return_tensors="pt", add_generation_prompt=True
).to(device)
out = model.generate(
input_ids=input_ids,
max_length=2000,
temperature=0.9,
top_p=0.7,
eos_token_id=tokenizer.eos_token_id,
)
decoded = tokenizer.batch_decode(out)
assistant_message = (
decoded[0].split("<|assistant|>\n")[-1].replace(eos, "")
)
print(assistant_message)
```
## Gradio Demo
```sh
git clone https://github.com/mrm8488/mamba-chat.git
cd mamba-chat
pip install -r requirements.txt
pip install -q gradio==4.8.0
python app.py \
--model clibrain/mamba-2.8b-instruct-openhermes \
--share
```
## Evaluations
Coming soon!
## Acknowledgments
Thanks to [mamba-chat](https://github.com/havenhq/mamba-chat/tree/main) for heavily inspiring our work |