Commit
•
4c53d47
1
Parent(s):
0ab711f
Create model card (#1)
Browse files- Create model card (dc6871874c2cc635d34d0f61c47a7af2eda2b7a4)
- Update README.md (1e4dd958ec290ac197ff9c8869de42b7d7702bf4)
- Update README.md (8315dcabcaa219d38cbbbec76e5bbec947181186)
- Update README.md (4bd28af77e457999364dcce722348a84443737c6)
Co-authored-by: Yozh <justheuristic@users.noreply.huggingface.co>
README.md
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
tags:
|
| 4 |
+
- llama
|
| 5 |
+
- facebook
|
| 6 |
+
- meta
|
| 7 |
+
- llama-2
|
| 8 |
+
- conversational
|
| 9 |
+
- text-generation-inference
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
An official quantization of [meta-llama/Llama-2-7b](https://huggingface.co/meta-llama/Llama-2-7b) using [PV-Tuning](https://arxiv.org/abs/2405.14852) on top of [AQLM](https://arxiv.org/abs/2401.06118).
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
For this quantization, we used 1 codebook of 16 bits for groups of 8 weights.
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
| Model | AQLM scheme | WikiText 2 PPL | Model size, Gb | Hub link |
|
| 19 |
+
|------------|-------------|----------------|----------------|--------------------------------------------------------------------------|
|
| 20 |
+
| Llama-2-7b (this) | 1x16 | 5.68 | 2.4 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-1x16-hf) |
|
| 21 |
+
| Llama-2-7b | 2x8 | 5.90 | 2.2 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-7b-AQLM-PV-2Bit-2x8-hf) |
|
| 22 |
+
| Llama-2-13b| 1x16 | 5.05 | 4.1 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-13b-AQLM-PV-2Bit-1x16-hf)|
|
| 23 |
+
| Llama-2-70b| 1x16 | 3.78 | 18.8 | [Link](https://huggingface.co/ISTA-DASLab/Llama-2-70b-AQLM-PV-2Bit-1x16-hf)|
|
| 24 |
+
|
| 25 |
+
The 1x16g16 (1-bit) models are on the way, as soon as we update the inference lib with their respective kernels.
|
| 26 |
+
|
| 27 |
+
To learn more about the inference, as well as the information on how to quantize models yourself, please refer to the [official GitHub repo](https://github.com/Vahe1994/AQLM).
|
| 28 |
+
The original code for PV-Tuning can be found in the [AQLM@pv-tuning](https://github.com/Vahe1994/AQLM/tree/pv-tuning) branch.
|
| 29 |
+
|