Downloads · 30 days
16
12% of all-time downloads
ISTA-DASLab/Phi-3-medium-4k-instruct-AQLM-PV-2Bit-1x16-hf
Phi-3-medium-4k-instruct-AQLM-PV-2Bit-1x16-hf is a text generation model from ISTA-DASLab. Use it when you need the model to write or continue text. It is set up for transformers.
Official quantization of Mistral-7B-v0.1 using PV-Tuning on top of AQLM.
Downloads · 30 days
16
12% of all-time downloads
All-time downloads
131
Public
Parameters
2.1B
4.2 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors4.2 GB · 100%
How the weights are stored.
I161.7B · 80%
From the Hugging Face model README
Official quantization of Mistral-7B-v0.1 using PV-Tuning on top of AQLM.
For this quantization, we used 1 codebook of 16 bits for groups of 8 weights.
Results (0-shot acc):
Results:
| Model | Quantization | WikiText-2 | C4 | Model size, Gb |
|---|---|---|---|---|
| microsoft/Phi-3-medium-4k-instruct | None | 27.9 | ||
| 1x16g8 (2-bit, model link) | 5.18 | 8.56 | 4.2Gb | |
| 1x16g16 (1-bit, this model) | 7.42 | 10.40 | 2.7Gb |
Phi-3-medium is not included in the original PV-Tuining paper. As of yet, we did not have the bandwidth to evaluate it properly. We hope to eventually run the zero-shot evaluation suite, or you can help us by running it yourself and opening a pull-request to the readme!
In general, we always recommend the 2-bit models for best accuracy-size trade-offs. If tempted to use the 1-bit model, try a smaller model , e.g. Phi-3-mini quantized with AQLM+PV (quantized model link) and compare the results, or check our AQLM+PV collection for a more appropriate size.
To learn more about the inference, as well as the information on how to quantize models yourself, please refer to the official GitHub repo. The original code for PV-Tuning can be found in the AQLM@pv-tuning branch.