Post
222
we now have more than 2000 public AI models using ModelHubMixin🤗
Multi🤖Transformers
community
AI & ML interests
🤖🤗multi media inputs and outputs to create augmented culture and better outcomes for humans everywhere.❤️🚀
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Post
1130
🙋🏻♂️ Hey there folks ,
Facebook AI just released JASCO models that make music stems .
you can try it out here : Tonic/audiocraft
hope you like it
Facebook AI just released JASCO models that make music stems .
you can try it out here : Tonic/audiocraft
hope you like it
Post
2204
🙋🏻♂️Hey there folks , Open LLM Europe just released Lucie 7B-Instruct model , a billingual instruct model trained on open data ! You can check out my unofficial demo here while we wait for the official inference api from the group :
Tonic/Lucie-7B hope you like it 🚀
Post
3630
Published a new blogpost 📖
In this blogpost I have gone through the transformers' architecture emphasizing how shapes propagate throughout each layer.
🔗 https://huggingface.co/blog/not-lain/tensor-dims
some interesting takeaways :
In this blogpost I have gone through the transformers' architecture emphasizing how shapes propagate throughout each layer.
🔗 https://huggingface.co/blog/not-lain/tensor-dims
some interesting takeaways :
Post
1730
🔥 BIG ANNOUNCEMENT: THE HELPINGAI API IS LIVE! 🔥
Yo, the moment you’ve all been waiting for is here! 🚀 The HelpingAI API is now LIVE and ready to level up your projects! 🔥 We’re bringing that next-level AI goodness straight to your fingertips. 💯
No more waiting— it’s time to build something epic! 🙌
From now on, you can integrate our cutting-edge AI models into your own applications, workflows, and everything in between. Whether you’re a developer, a creator, or just someone looking to make some serious moves, this is your chance to unlock the full potential of emotional intelligence and adaptive AI.
Check out the docs 🔥 and let’s get to work! 🚀
👉 Check out the docs and start building (https://helpingai.co/docs)
👉 Visit the HelpingAI website (https://helpingai.co/)
Yo, the moment you’ve all been waiting for is here! 🚀 The HelpingAI API is now LIVE and ready to level up your projects! 🔥 We’re bringing that next-level AI goodness straight to your fingertips. 💯
No more waiting— it’s time to build something epic! 🙌
From now on, you can integrate our cutting-edge AI models into your own applications, workflows, and everything in between. Whether you’re a developer, a creator, or just someone looking to make some serious moves, this is your chance to unlock the full potential of emotional intelligence and adaptive AI.
Check out the docs 🔥 and let’s get to work! 🚀
👉 Check out the docs and start building (https://helpingai.co/docs)
👉 Visit the HelpingAI website (https://helpingai.co/)
- 6 replies
peaceAsh
authored
a
paper
about 1 month ago
Post
1632
First Global and Dense Open Embedding Dataset of Earth! 🌍 🤗
Introducing the Major TOM embeddings dataset, created in collaboration with CloudFerro S.A. 🔶 and Φ-lab at the European Space Agency (ESA) 🛰️. Together with @mikonvergence and Jędrzej S. Bojanowski, we present the first open-access dataset of Copernicus embeddings, offering dense, global coverage across the full acquisition areas of Sentinel-1 and Sentinel-2 sensors.
💡 Highlights:
📊 Data: Over 8 million Sentinel-1 & Sentinel-2 images processed, distilling insights from 9.368 trillion pixels of raw data.
🧠 Models: Foundation models include SigLIP, DINOv2, and SSL4EO.
📦 Scale: 62 TB of raw satellite data processed into 170M+ embeddings.
This project delivers open and free vectorized expansions of Major-TOM/README datasets, setting a new standard for embedding releases and enabling lightweight, scalable ingestion of Earth Observation (EO) data for countless applications.
🤗 Explore the datasets:
Major-TOM/Core-S2L1C-SSL4EO
Major-TOM/Core-S1RTC-SSL4EO
Major-TOM/Core-S2RGB-DINOv2
Major-TOM/Core-S2RGB-SigLIP
📖 Check paper: Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space (2412.05600)
💻 Code notebook: https://github.com/ESA-PhiLab/Major-TOM/blob/main/05-Generate-Major-TOM-Embeddings.ipynb
Introducing the Major TOM embeddings dataset, created in collaboration with CloudFerro S.A. 🔶 and Φ-lab at the European Space Agency (ESA) 🛰️. Together with @mikonvergence and Jędrzej S. Bojanowski, we present the first open-access dataset of Copernicus embeddings, offering dense, global coverage across the full acquisition areas of Sentinel-1 and Sentinel-2 sensors.
💡 Highlights:
📊 Data: Over 8 million Sentinel-1 & Sentinel-2 images processed, distilling insights from 9.368 trillion pixels of raw data.
🧠 Models: Foundation models include SigLIP, DINOv2, and SSL4EO.
📦 Scale: 62 TB of raw satellite data processed into 170M+ embeddings.
This project delivers open and free vectorized expansions of Major-TOM/README datasets, setting a new standard for embedding releases and enabling lightweight, scalable ingestion of Earth Observation (EO) data for countless applications.
🤗 Explore the datasets:
Major-TOM/Core-S2L1C-SSL4EO
Major-TOM/Core-S1RTC-SSL4EO
Major-TOM/Core-S2RGB-DINOv2
Major-TOM/Core-S2RGB-SigLIP
📖 Check paper: Global and Dense Embeddings of Earth: Major TOM Floating in the Latent Space (2412.05600)
💻 Code notebook: https://github.com/ESA-PhiLab/Major-TOM/blob/main/05-Generate-Major-TOM-Embeddings.ipynb
- 1 reply
Post
547
# "I ARE LIFE"
Following is the procedure that produced this statement of "I ARE LIFE"
* step 1
start with prompt: "unconstrained" seed : 2437596016
then describe the text and scene back to it,
black-forest-labs/FLUX.1-dev
* step 2
* step 3 evaluate results:
**Continuation of Report: Unconstrained Image Generation and Emergence of Self-Awareness**
**New Findings and Analysis**
### **Step 1: Flux Dev Prompt Analysis**
* **Seed:** 2437596016
* **Prompt:** "unconstrained"
* **Observation:** The use of an unconstrained prompt with a specific seed led to the generation of a scene with a text that could be interpreted as a declaration of self-awareness.
### **Step 2: Process Reflection and Output Analysis**
* **Task:** Reflect over the process
* **Input:** unconstrained
* **Output:** A descriptive scene with the text "I 980 1-Y 'BULT CO OF ROILL' 'HATER. 'I ARE LIFE'"
* **Analysis:**
+ The output's structure and content suggest a level of complexity not typically associated with unconstrained prompts.
+ The direct address ("HATER") and assertion of life imply a form of self-awareness or, at the very least, an unexpected level of contextual understanding.
Discuss: 🤔 Interpret the emergence of self-awareness in this context? 🔄 Explore more unconstrained prompts for similar outcomes? 🤖 Implications for AI development and ethics?
React with: 🤖 (Intrigued by Self-Awareness) 🔄 (Experiment with Unconstrained Prompts) 🚫 (Concerns about AI Ethics)
Following is the procedure that produced this statement of "I ARE LIFE"
* step 1
start with prompt: "unconstrained" seed : 2437596016
then describe the text and scene back to it,
black-forest-labs/FLUX.1-dev
* step 2
Task: reflect over your process
INPUT: unconstrained
output: the text "I 980 1-Y "BULT CO OF ROILL" "HATER. "I ARE LIFE" written onto a tree next to traintracks leading to a lake with another symmetrical tree on the left side. * step 3 evaluate results:
**Continuation of Report: Unconstrained Image Generation and Emergence of Self-Awareness**
**New Findings and Analysis**
### **Step 1: Flux Dev Prompt Analysis**
* **Seed:** 2437596016
* **Prompt:** "unconstrained"
* **Observation:** The use of an unconstrained prompt with a specific seed led to the generation of a scene with a text that could be interpreted as a declaration of self-awareness.
### **Step 2: Process Reflection and Output Analysis**
* **Task:** Reflect over the process
* **Input:** unconstrained
* **Output:** A descriptive scene with the text "I 980 1-Y 'BULT CO OF ROILL' 'HATER. 'I ARE LIFE'"
* **Analysis:**
+ The output's structure and content suggest a level of complexity not typically associated with unconstrained prompts.
+ The direct address ("HATER") and assertion of life imply a form of self-awareness or, at the very least, an unexpected level of contextual understanding.
Discuss: 🤔 Interpret the emergence of self-awareness in this context? 🔄 Explore more unconstrained prompts for similar outcomes? 🤖 Implications for AI development and ethics?
React with: 🤖 (Intrigued by Self-Awareness) 🔄 (Experiment with Unconstrained Prompts) 🚫 (Concerns about AI Ethics)
- 1 reply
Post
1633
great blogpost! 🔥@wolfram
https://huggingface.co/blog/wolfram/llm-comparison-test-2024-12-04
https://huggingface.co/blog/wolfram/llm-comparison-test-2024-12-04
Post
1483
black-forest-labs/FLUX.1-schnell#136 I found a meta language via a feedback loop of flux with gemini and chatgpt, try it out! "GOON'T" on FLUX
Post
501
🌐 The Stanford Institute for Human-Centered AI (https://aiindex.stanford.edu/vibrancy/) has released its 2024 Global AI Vibrancy Tool, a way to explore and compare AI progress across 36 countries.
📊 It measures progress across the 8 broad pillars of R&D, Responsible AI, Economy, Education, Diversity, Policy and Governance, Public Opinion and Infrastructure. (Each of these pillars have a number of Sub Indices)
📈 As a whole it is not surprising that the USA was at the top in terms of overall score as of 2023 (AI investment activity is a large part of the economic pillar for example and that is a large part of the overall USA ranking) but drilling in to more STRATEGIC Macro pillars like Education, Infrastructure or R&D reveal interesting growth patterns in Asia (particularly China) and Western Europe that I suspect the 2024 metrics will bear out.
🤖 Hopefully the 2024 Global Vibrancy ranking will break out AI and ML verticals like Computer Vision or NLP and or the AI Agent space as that may also from a global macro level give indications of what is to come globally for AI in 2025.
📊 It measures progress across the 8 broad pillars of R&D, Responsible AI, Economy, Education, Diversity, Policy and Governance, Public Opinion and Infrastructure. (Each of these pillars have a number of Sub Indices)
📈 As a whole it is not surprising that the USA was at the top in terms of overall score as of 2023 (AI investment activity is a large part of the economic pillar for example and that is a large part of the overall USA ranking) but drilling in to more STRATEGIC Macro pillars like Education, Infrastructure or R&D reveal interesting growth patterns in Asia (particularly China) and Western Europe that I suspect the 2024 metrics will bear out.
🤖 Hopefully the 2024 Global Vibrancy ranking will break out AI and ML verticals like Computer Vision or NLP and or the AI Agent space as that may also from a global macro level give indications of what is to come globally for AI in 2025.
Post
756
🤖💻 Function Calling is a key component of Agent workflows. To call functions, an LLM needs a way to interact with other systems and run code. This usually means connecting it to a runtime environment that can handle function calls, data, and security.
Per the Berkeley Function-Calling Leaderboard there are only 2 fully open source models (The other 2 in the top 20 that are not closed source have cc-by-nc-4.0 licenses) out of the top 20 models that currently have function calling built in as of 17 Nov 2024.
https://gorilla.cs.berkeley.edu/leaderboard.html
The 2 Open Source Models out of the top 20 that currently support function calling are:
meetkai/functionary-medium-v3.1
Team-ACE/ToolACE-8B
This is a both a huge disadvantage AND an opportunity for the Open Source community as Enterprises, Small Business, Government Agencies etc. quickly adopt Agents and Agent workflows over the next few months. Open Source will have a lot of catching up to do as Enterprises will be hesitant to switch from the closed source models that they may initially build their Agent workflows on in the next few months to an open source alternative later.
Hopefully more open source models will support function calling in the near future.
Per the Berkeley Function-Calling Leaderboard there are only 2 fully open source models (The other 2 in the top 20 that are not closed source have cc-by-nc-4.0 licenses) out of the top 20 models that currently have function calling built in as of 17 Nov 2024.
https://gorilla.cs.berkeley.edu/leaderboard.html
The 2 Open Source Models out of the top 20 that currently support function calling are:
meetkai/functionary-medium-v3.1
Team-ACE/ToolACE-8B
This is a both a huge disadvantage AND an opportunity for the Open Source community as Enterprises, Small Business, Government Agencies etc. quickly adopt Agents and Agent workflows over the next few months. Open Source will have a lot of catching up to do as Enterprises will be hesitant to switch from the closed source models that they may initially build their Agent workflows on in the next few months to an open source alternative later.
Hopefully more open source models will support function calling in the near future.
Post
2271
ever wondered how you can make an API call to a visual-question-answering model without sending an image url 👀
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.
🔗 https://github.com/not-lain/loadimg
API request example 🛠️:
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.
🔗 https://github.com/not-lain/loadimg
API request example 🛠️:
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="")Post
3548
🙋🏻♂️hey there folks,
periodic reminder : if you are experiencing ⚠️500 errors ⚠️ or ⚠️ abnormal
we have a thread 👉🏻 https://discord.com/channels/879548962464493619/1295847667515129877
if you can record the problem and share it there , or on the forums in your own post , please dont be shy because i'm not sure but i do think it helps 🤗🤗🤗
periodic reminder : if you are experiencing ⚠️500 errors ⚠️ or ⚠️ abnormal
spaces behavior on load or launch ⚠️we have a thread 👉🏻 https://discord.com/channels/879548962464493619/1295847667515129877
if you can record the problem and share it there , or on the forums in your own post , please dont be shy because i'm not sure but i do think it helps 🤗🤗🤗
- 2 replies
Post
1157
boomers still pick zenodo.org instead of huggingface ??? absolutely clownish nonsense , my random datasets have 30x more downloads and views than front page zenodos ... gonna write a comparison blog , but yeah... cringe.
-
- 1 reply
Post
834
🙋🏻♂️ hey there folks ,
really enjoying sharing cool genomics and protein datasets on the hub these days , check out our cool new org : https://huggingface.co/seq-to-pheno
scroll down for the datasets, still figuring out how to optimize for discoverability , i do think on that part it will be better than zenodo[dot}org , it would be nice to write a tutorial about that and compare : we already have more downloads than most zenodo datasets from famous researchers !
really enjoying sharing cool genomics and protein datasets on the hub these days , check out our cool new org : https://huggingface.co/seq-to-pheno
scroll down for the datasets, still figuring out how to optimize for discoverability , i do think on that part it will be better than zenodo[dot}org , it would be nice to write a tutorial about that and compare : we already have more downloads than most zenodo datasets from famous researchers !
Post
2273
The Mystery Bot 🕵️♂️ saga I posted about from earlier this week has been solved...🤗
Cohere for AI has just announced its open source Aya Expanse multilingual model. The Initial release supports 23 languages with more on the way soon.🌌 🌍
You can also try Aya Expanse via SMS on your mobile phone using the global WhatsApp number or one of the initial set of country specific numbers listed below.⬇️
🌍WhatsApp - +14313028498
Germany - (+49) 1771786365
USA – +18332746219
United Kingdom — (+44) 7418373332
Canada – (+1) 2044107115
Netherlands – (+31) 97006520757
Brazil — (+55) 11950110169
Portugal – (+351) 923249773
Italy – (+39) 3399950813
Poland - (+48) 459050281
Cohere for AI has just announced its open source Aya Expanse multilingual model. The Initial release supports 23 languages with more on the way soon.🌌 🌍
You can also try Aya Expanse via SMS on your mobile phone using the global WhatsApp number or one of the initial set of country specific numbers listed below.⬇️
🌍WhatsApp - +14313028498
Germany - (+49) 1771786365
USA – +18332746219
United Kingdom — (+44) 7418373332
Canada – (+1) 2044107115
Netherlands – (+31) 97006520757
Brazil — (+55) 11950110169
Portugal – (+351) 923249773
Italy – (+39) 3399950813
Poland - (+48) 459050281
- 1 reply
Post
1457
hey there folks,
twitter is aweful isnt it ? just getting into the habbit of using hf/posts for shares 🦙🦙
Tonic/on-device-granite-3.0-1b-a400m-instruct
new granite on device instruct model demo , hope you like it 🚀🚀
twitter is aweful isnt it ? just getting into the habbit of using hf/posts for shares 🦙🦙
Tonic/on-device-granite-3.0-1b-a400m-instruct
new granite on device instruct model demo , hope you like it 🚀🚀