Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,39 @@
|
|
1 |
-
---
|
2 |
-
|
3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
tags:
|
3 |
+
- mamba2
|
4 |
+
license: mit
|
5 |
+
library_name: transformers
|
6 |
+
---
|
7 |
+
|
8 |
+
# mamba2-1.3b-hf
|
9 |
+
|
10 |
+
Converted files of the original model at [mamba2-1.3b](https://huggingface.co/state-spaces/mamba2-1.3b) to HF transformers compatible formats.
|
11 |
+
Not affiliated with both the original authors or hf.
|
12 |
+
|
13 |
+
## Usage
|
14 |
+
```python
|
15 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
16 |
+
|
17 |
+
tokenizer = AutoTokenizer.from_pretrained("AntonV/mamba2-1.3b-hf")
|
18 |
+
model = AutoModelForCausalLM.from_pretrained("AntonV/mamba2-1.3b-hf")
|
19 |
+
|
20 |
+
input_ids = tokenizer("Hey how are you doing?", return_tensors="pt")["input_ids"]
|
21 |
+
out = model.generate(input_ids, max_new_tokens=10)
|
22 |
+
print(tokenizer.batch_decode(out))
|
23 |
+
```
|
24 |
+
|
25 |
+
|
26 |
+
## Citation
|
27 |
+
|
28 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
29 |
+
|
30 |
+
**BibTeX:**
|
31 |
+
|
32 |
+
```bibtex
|
33 |
+
@inproceedings{mamba2,
|
34 |
+
title={Transformers are {SSM}s: Generalized Models and Efficient Algorithms Through Structured State Space Duality},
|
35 |
+
author={Dao, Tri and Gu, Albert},
|
36 |
+
booktitle={International Conference on Machine Learning (ICML)},
|
37 |
+
year={2024}
|
38 |
+
}
|
39 |
+
```
|