aashish1904
commited on
Commit
•
4fda491
1
Parent(s):
d5c1f8a
Upload README.md with huggingface_hub
Browse files
README.md
ADDED
@@ -0,0 +1,60 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
|
2 |
+
---
|
3 |
+
|
4 |
+
license: gpl-3.0
|
5 |
+
datasets:
|
6 |
+
- Orion-zhen/kto-gutenberg
|
7 |
+
language:
|
8 |
+
- zh
|
9 |
+
- en
|
10 |
+
base_model:
|
11 |
+
- Orion-zhen/Qwen2.5-7B-Instruct-Uncensored
|
12 |
+
pipeline_tag: text-generation
|
13 |
+
|
14 |
+
---
|
15 |
+
|
16 |
+
[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
|
17 |
+
|
18 |
+
|
19 |
+
# QuantFactory/Qwen2.5-7B-Gutenberg-KTO-GGUF
|
20 |
+
This is quantized version of [Orion-zhen/Qwen2.5-7B-Gutenberg-KTO](https://huggingface.co/Orion-zhen/Qwen2.5-7B-Gutenberg-KTO) created using llama.cpp
|
21 |
+
|
22 |
+
# Original Model Card
|
23 |
+
|
24 |
+
|
25 |
+
# Qwen2.5-7B-Gutenberg-KTO
|
26 |
+
|
27 |
+
This model is fine tuned over gutenberg datasets using kto strategy. It's my first time to use kto strategy, and I'm not sure how the model actually performs.
|
28 |
+
|
29 |
+
Compared to those large companies which remove accessories such as charger and cables from packages, I have achieved **real** environment protection by **truly** reducing energy consumption, rather than shifting costs to consumers.
|
30 |
+
|
31 |
+
Checkout GGUF here: [Orion-zhen/Qwen2.5-7B-Gutenberg-KTO-Q6_K-GGUF](https://huggingface.co/Orion-zhen/Qwen2.5-7B-Gutenberg-KTO-Q6_K-GGUF)
|
32 |
+
|
33 |
+
## Details
|
34 |
+
|
35 |
+
### Platform
|
36 |
+
|
37 |
+
~~I randomly grabbed some rubbish from a second-hand market and built a PC~~
|
38 |
+
|
39 |
+
I carefully selected various dedicated hardwares and constructed an incomparable home server, which I entitled the **Great Server**:
|
40 |
+
|
41 |
+
- CPU: Intel Core i3-4160
|
42 |
+
- Memory: 8G DDR3, single channel
|
43 |
+
- GPU: Tesla P4, TDP 75W, boasting its **Eco friendly energy consumption**
|
44 |
+
- Disk: 1TB M.2 NVME, PCIe 4.0
|
45 |
+
|
46 |
+
### Training
|
47 |
+
|
48 |
+
To practice the **eco-friendly training**, I utilized various methods, including adam-mini, qlora and unsloth, to minimize VRAM and energy usage, as well as accelerating training speed.
|
49 |
+
|
50 |
+
- dataset: [Orion-zhen/kto-gutenberg](https://huggingface.co/datasets/Orion-zhen/kto-gutenberg)
|
51 |
+
- epoch: 2
|
52 |
+
- gradient accumulation: 8
|
53 |
+
- batch size: 1
|
54 |
+
- KTO perf beta: 0.1
|
55 |
+
|
56 |
+
### Train log
|
57 |
+
|
58 |
+
![training_loss](./training_loss.png)
|
59 |
+
|
60 |
+
![training_eval_loss](./training_eval_loss.png)
|