Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,42 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
tags:
|
3 |
+
- fp8
|
4 |
+
language:
|
5 |
+
- en
|
6 |
+
base_model: Sao10K/MN-12B-Lyra-v3
|
7 |
+
---
|
8 |
+
|
9 |
+
Original Model: https://huggingface.co/Sao10K/MN-12B-Lyra-v3
|
10 |
+
|
11 |
+
Quantized with FP8 using https://github.com/neuralmagic/AutoFP8
|
12 |
+
|
13 |
+
Script:
|
14 |
+
```python
|
15 |
+
from datasets import load_dataset
|
16 |
+
from transformers import AutoTokenizer
|
17 |
+
|
18 |
+
from auto_fp8 import AutoFP8ForCausalLM, BaseQuantizeConfig
|
19 |
+
|
20 |
+
pretrained_model_dir = "Sao10K/MN-12B-Lyra-v3"
|
21 |
+
quantized_model_dir = "MN-12B-Lyra-v3-FP8"
|
22 |
+
|
23 |
+
tokenizer = AutoTokenizer.from_pretrained(pretrained_model_dir, use_fast=True, model_max_length=4096)
|
24 |
+
tokenizer.pad_token = tokenizer.eos_token
|
25 |
+
|
26 |
+
ds = load_dataset("mgoin/ultrachat_2k", split="train_sft").select(range(512))
|
27 |
+
examples = [tokenizer.apply_chat_template(batch["messages"], tokenize=False) for batch in ds]
|
28 |
+
examples = tokenizer(examples, padding=True, truncation=True, return_tensors="pt").to("cuda")
|
29 |
+
|
30 |
+
quantize_config = BaseQuantizeConfig(
|
31 |
+
quant_method="fp8",
|
32 |
+
activation_scheme="static",
|
33 |
+
ignore_patterns=["re:.*lm_head"],
|
34 |
+
)
|
35 |
+
|
36 |
+
model = AutoFP8ForCausalLM.from_pretrained(
|
37 |
+
pretrained_model_dir, quantize_config=quantize_config
|
38 |
+
)
|
39 |
+
|
40 |
+
model.quantize(examples)
|
41 |
+
model.save_quantized(quantized_model_dir)
|
42 |
+
```
|