Stable Diffusion Community (Unofficial, Non-profit)

community

AI & ML interests

Enhance and upgrade SD-models

sd-community's activity

not-lainΒ 
posted an update about 5 hours ago
AtAndDevΒ 
posted an update about 22 hours ago
view post
Post
786
everywhere i go i see his face
Delta-VectorΒ 
posted an update 3 days ago
AtAndDevΒ 
posted an update 8 days ago
view post
Post
469
Deepseek gang on fire fr fr
AtAndDevΒ 
posted an update 10 days ago
view post
Post
1572
R1 is out! And with a lot of other R1 releated models...
not-lainΒ 
posted an update 13 days ago
view post
Post
1155
we now have more than 2000 public AI models using ModelHubMixinπŸ€—
not-lainΒ 
posted an update 18 days ago
view post
Post
3928
Published a new blogpost πŸ“–
In this blogpost I have gone through the transformers' architecture emphasizing how shapes propagate throughout each layer.
πŸ”— https://huggingface.co/blog/not-lain/tensor-dims
some interesting takeaways :
1aurentΒ 
posted an update 30 days ago
ehristoforuΒ 
posted an update about 1 month ago
view post
Post
3133
βœ’οΈ Ultraset - all-in-one dataset for SFT training in Alpaca format.
fluently-sets/ultraset

❓ Ultraset is a comprehensive dataset for training Large Language Models (LLMs) using the SFT (instruction-based Fine-Tuning) method. This dataset consists of over 785 thousand entries in eight languages, including English, Russian, French, Italian, Spanish, German, Chinese, and Korean.

🀯 Ultraset solves the problem faced by users when selecting an appropriate dataset for LLM training. It combines various types of data required to enhance the model's skills in areas such as text writing and editing, mathematics, coding, biology, medicine, finance, and multilingualism.

πŸ€— For effective use of the dataset, it is recommended to utilize only the "instruction," "input," and "output" columns and train the model for 1-3 epochs. The dataset does not include DPO or Instruct data, making it suitable for training various types of LLM models.

❇️ Ultraset is an excellent tool to improve your language model's skills in diverse knowledge areas.
AtAndDevΒ 
posted an update about 1 month ago
view post
Post
453
@s3nh Hey man check your discord! Got some news.
  • 4 replies
Β·
eienmojikiΒ 
posted an update about 2 months ago
view post
Post
1494
πŸ‘€ Introducing 2048 Game API: A RESTful API for the Classic Puzzle Game 🧩

I'm excited to share my latest project, 2048 Game API, a RESTful API that allows you to create, manage, and play games of 2048, a popular puzzle game where players slide numbered tiles to combine them and reach the goal of getting a tile with the value of 2048.

⭐ Features
Create new games with customizable board sizes (3-8)
Make moves (up, down, left, right) and get the updated game state
Get the current game state, including the board, score, and game over status
Delete games
Generate images of the game board with customizable themes (light and dark)

πŸ”— API Endpoints
POST /api/games - Create a new game
GET /api/games/:gameId - Get the current game state
POST /api/games/:gameId/move - Make a move (up, down, left, right)
DELETE /api/games/:gameId - Delete a game
GET /api/games/:gameId/image - Generate an image of the game board

🧩 Example Use Cases
- Create a new game with a 4x4 board:
curl -X POST -H "Content-Type: application/json" -d '{"size": 4}' http://localhost:3000/api/games

- Make a move up:
curl -X POST -H "Content-Type: application/json" -d '{"direction": "up"}' http://localhost:3000/api/games/:gameId/move

- Get the current game state:
curl -X GET http://localhost:3000/api/games/:gameId

πŸ’• Try it out!
- Demo: eienmojiki/2048
- Source: https://github.com/kogakisaki/koga-2048
- You can try out the API by running the server locally or using a tool like Postman to send requests to the API. I hope you enjoy playing 2048 with this API!

Let me know if you have any questions or feedback!

🐧 Mouse1 is our friend🐧
not-lainΒ 
posted an update 3 months ago
view post
Post
2292
ever wondered how you can make an API call to a visual-question-answering model without sending an image url πŸ‘€

you can do that by converting your local image to base64 and sending it to the API.

recently I made some changes to my library "loadimg" that allows you to make converting images to base64 a breeze.
πŸ”— https://github.com/not-lain/loadimg

API request example πŸ› οΈ:
from loadimg import load_img
from huggingface_hub import InferenceClient

# or load a local image
my_b64_img = load_img(imgPath_url_pillow_or_numpy ,output_type="base64" ) 

client = InferenceClient(api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")

messages = [
	{
		"role": "user",
		"content": [
			{
				"type": "text",
				"text": "Describe this image in one sentence."
			},
			{
				"type": "image_url",
				"image_url": {
					"url": my_b64_img # base64 allows using images without uploading them to the web
				}
			}
		]
	}
]

stream = client.chat.completions.create(
    model="meta-llama/Llama-3.2-11B-Vision-Instruct", 
	messages=messages, 
	max_tokens=500,
	stream=True
)

for chunk in stream:
    print(chunk.choices[0].delta.content, end="")
KingNishΒ 
posted an update 4 months ago
KingNishΒ 
posted an update 4 months ago
view post
Post
8005
Exciting news! Introducing super-fast AI video assistant, currently in beta. With a minimum latency of under 500ms and an average latency of just 600ms.

DEMO LINK:
KingNish/Live-Video-Chat
  • 1 reply
Β·
KingNishΒ 
posted an update 4 months ago
KingNishΒ 
posted an update 4 months ago
view post
Post
3584
Mistral Nemo is better than many models in 1st grader level reasoning.