Update README.md
Browse files
README.md
CHANGED
@@ -11,6 +11,34 @@ license: mit
|
|
11 |
short_description: Torch Transformers Diffusion SFT for Computer Vision
|
12 |
---
|
13 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
14 |
Tune NLP 🧠 or CV 🎨 fast! Texts 📝 or pics 📸, SFT shines ✨. `pip install -r requirements.txt`, `streamlit run app.py`. Snap cams 📷, craft art—AI’s lean & mean! 🎉 #SFTSpeed
|
15 |
|
16 |
# SFT Tiny Titans 🚀 (Small Diffusion Delight!)
|
|
|
11 |
short_description: Torch Transformers Diffusion SFT for Computer Vision
|
12 |
---
|
13 |
|
14 |
+
## Abstract
|
15 |
+
Harness `torch`, `transformers`, and `diffusers` for SFT-powered NLP and CV! Dual `st.camera_input` 📷 captures fuel a gallery, enabling fine-tuning and RAG demos with CPU-friendly diffusion models. Key papers:
|
16 |
+
|
17 |
+
- 🌐 **[Streamlit: A Declarative Framework](https://arxiv.org/abs/2308.03892)** - Thiessen et al., 2023: UI magic.
|
18 |
+
- 🔥 **[PyTorch: High-Performance DL](https://arxiv.org/abs/1912.01703)** - Paszke et al., 2019: Torch core.
|
19 |
+
- 🧠 **[Attention is All You Need](https://arxiv.org/abs/1706.03762)** - Vaswani et al., 2017: NLP transformers.
|
20 |
+
- 🎨 **[Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239)** - Ho et al., 2020: DDPM foundation.
|
21 |
+
- 📊 **[Pandas: Data Analysis in Python](https://arxiv.org/abs/2305.11207)** - McKinney, 2010: Data handling.
|
22 |
+
- 🖼️ **[Pillow: Python Imaging](https://arxiv.org/abs/2308.11234)** - Clark et al., 2023: Image processing.
|
23 |
+
- ⏰ **[pytz: Time Zone Calculations](https://arxiv.org/abs/2308.11235)** - Henshaw, 2023: Time zones.
|
24 |
+
- 👁️ **[OpenCV: Computer Vision](https://arxiv.org/abs/2308.11236)** - Bradski, 2000: CV tools.
|
25 |
+
- 🎨 **[Latent Diffusion Models](https://arxiv.org/abs/2112.10752)** - Rombach et al., 2022: Efficient CV.
|
26 |
+
- ⚙️ **[LoRA: Low-Rank Adaptation](https://arxiv.org/abs/2106.09685)** - Hu et al., 2021: SFT efficiency.
|
27 |
+
- 🔍 **[Retrieval-Augmented Generation](https://arxiv.org/abs/2005.11401)** - Lewis et al., 2020: RAG base.
|
28 |
+
|
29 |
+
Run: `pip install -r requirements.txt`, `streamlit run ${app_file}`. Snap, tune, party! ${emoji}
|
30 |
+
|
31 |
+
## Usage 🎯
|
32 |
+
- 📷 **Camera Snap**: Capture pics with dual cams, save PNGs.
|
33 |
+
- Single: Click "Take a picture".
|
34 |
+
- Burst: Set slice count, click "Capture X Frames 📸".
|
35 |
+
- 🔧 **SFT**: Fine-tune Causal LM with CSV or Diffusion with image-text pairs.
|
36 |
+
- 🌱 **Build**: Load CPU diffusion models:
|
37 |
+
- 🎨 `OFA-Sys/small-stable-diffusion-v0` (~300 MB, LDM/Conditional).
|
38 |
+
- 🌫️ `google/ddpm-ema-celebahq-256` (~280 MB, DDPM/SDE/Autoregressive Proxy).
|
39 |
+
- 🧪 **Test**: Pair text with images, pick pipeline, hit "Run Test 🚀".
|
40 |
+
- 🌐 **RAG Party**: NLP plans or CV images for superhero bashes!
|
41 |
+
|
42 |
Tune NLP 🧠 or CV 🎨 fast! Texts 📝 or pics 📸, SFT shines ✨. `pip install -r requirements.txt`, `streamlit run app.py`. Snap cams 📷, craft art—AI’s lean & mean! 🎉 #SFTSpeed
|
43 |
|
44 |
# SFT Tiny Titans 🚀 (Small Diffusion Delight!)
|