CyberHarem

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AI & ML interests

Anime Bishojo. This organization is only for waifus' datasets and loras

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anohaΒ  updated a Space 3 months ago
CyberHarem/README
narugoΒ  updated a model 4 months ago
CyberHarem/venti_genshin
narugoΒ  updated a model 4 months ago
CyberHarem/zhongli_genshin
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CyberHarem's activity

LewdiculousΒ 
posted an update 5 days ago
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1607
Hello fellow LLMers, just a quick notice that some of my activity will be moved into the AetherArchitectural Commuity and split with @Aetherarchio .

[here] https://huggingface.co/AetherArchitectural

All activity should be visible in the left side of my profile.
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s3nhΒ 
posted an update 5 days ago
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1589
Welcome back,

Small Language Models Enthusiasts and GPU Poor oss enjoyers lets connect.
Just created an organization which main target is to have fun with smaller models tuneable on consumer range GPUs, feel free to join and lets have some fun, much love ;3

https://huggingface.co/SmolTuners
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lunarfluΒ 
posted an update 19 days ago
not-lainΒ 
posted an update about 1 month ago
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1810
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="")
anohaΒ 
updated a Space 3 months ago
lunarfluΒ 
posted an update 4 months ago
not-lainΒ 
posted an update 5 months ago