text
Check this out: I trained an AI on huggingface posts! all of these are AI generated:
Check this out: I trained an AI on huggingface posts! all of these are AI generated:
new_line
text
----------
----------
new_line
text
Hello!
Hello!
new_line
new_line
text
I'm excited to share that my colleague 
I'm excited to share that my colleague 
mention
@felipeebert
felipeebert
text
 and I have released the largest Spanish LLM benchmark to date. 
 and I have released the largest Spanish LLM benchmark to date. 
new_line
new_line
text
We've developed the Spanish LLM Evaluation Benchmark (SLAB), a set of benchmarks designed to evaluate the ability of language models to understand, generate and translate in Spanish.   
We've developed the Spanish LLM Evaluation Benchmark (SLAB), a set of benchmarks designed to evaluate the ability of language models to understand, generate and translate in Spanish.   
new_line
new_line
text
SLAB includes five different benchmarks:
SLAB includes five different benchmarks:
new_line
text
- Sentiment Analysis: evaluate models' ability to detect and describe sentiment in natural language
- Sentiment Analysis: evaluate models' ability to detect and describe sentiment in natural language
new_line
text
- Fact Checking: evaluate models' ability to detect and refute factual errors in text
- Fact Checking: evaluate models' ability to detect and refute factual errors in text
new_line
text
- Question Answering: evaluate models' ability to answer questions in Spanish
- Question Answering: evaluate models' ability to answer questions in Spanish
new_line
text
- Open-ended Questions: evaluate models' ability to generate coherent responses in Spanish
- Open-ended Questions: evaluate models' ability to generate coherent responses in Spanish
new_line
text
- Translation: evaluate models' ability to translate in Spanish
- Translation: evaluate models' ability to translate in Spanish
new_line
new_line
text
SLAB is aligned with the latest Spanish LLM industry developments and includes the most recent models available on the market. We aim to keep our benchmarks up-to-date and relevant to the Spanish language ecosystem.
SLAB is aligned with the latest Spanish LLM industry developments and includes the most recent models available on the market. We aim to keep our benchmarks up-to-date and relevant to the Spanish language ecosystem.
new_line
new_line
text
SLAB is available at: 
SLAB is available at: 
link
https://huggingface.co/datasets/argilla/SLAB
https://huggingface.co/datasets/argilla/SLAB
text
. 
. 
new_line
new_line
text
If you would like to collaborate on building additional Spanish LLM benchmarks, let's discuss in the comments.
If you would like to collaborate on building additional Spanish LLM benchmarks, let's discuss in the comments.
new_line
new_line
text
🔗 SLAB Blog Post: 
🔗 SLAB Blog Post: 
link
https://argilla.com/blog/slab
https://argilla.com/blog/slab
new_line
text
----------
----------
new_line
text
Hello everyone,
Hello everyone,
new_line
new_line
text
I'm thrilled to announce the release of 
I'm thrilled to announce the release of 
new_line
new_line
link
https://huggingface.co/01-AI/01AI-GPT-4o
https://huggingface.co/01-AI/01AI-GPT-4o
text
 -
 -
new_line
new_line
text
A new family of models that brings the power of transformer AI to the masses.
A new family of models that brings the power of transformer AI to the masses.
new_line
new_line
text
This model is designed to be accessible and easy to use, while still offering high-quality results.
This model is designed to be accessible and easy to use, while still offering high-quality results.
new_line
new_line
text
Key features:
Key features:
new_line
text
- Small model size: only 23M parameters
- Small model size: only 23M parameters
new_line
text
- Supports text generation, image generation, and text-to-image tasks
- Supports text generation, image generation, and text-to-image tasks
new_line
text
- Data-efficient training with a lightweight tokenizer
- Data-efficient training with a lightweight tokenizer
new_line
text
- Optimized for efficient on-device usage
- Optimized for efficient on-device usage
new_line
text
- Uses the powerful transformer architecture to deliver high-quality results
- Uses the powerful transformer architecture to deliver high-quality results
new_line
new_line
text
Excited to see what you all think!
Excited to see what you all think!
new_line
new_line
link
https://huggingface.co/01-AI/01AI-GPT-4o
https://huggingface.co/01-AI/01AI-GPT-4o
Check this out: I trained an AI on huggingface posts! all of these are AI generated:
----------
Hello!

I'm excited to share that my colleague @felipeebert and I have released the largest Spanish LLM benchmark to date. 

We've developed the Spanish LLM Evaluation Benchmark (SLAB), a set of benchmarks designed to evaluate the ability of language models to understand, generate and translate in Spanish.   

SLAB includes five different benchmarks:
- Sentiment Analysis: evaluate models' ability to detect and describe sentiment in natural language
- Fact Checking: evaluate models' ability to detect and refute factual errors in text
- Question Answering: evaluate models' ability to answer questions in Spanish
- Open-ended Questions: evaluate models' ability to generate coherent responses in Spanish
- Translation: evaluate models' ability to translate in Spanish

SLAB is aligned with the latest Spanish LLM industry developments and includes the most recent models available on the market. We aim to keep our benchmarks up-to-date and relevant to the Spanish language ecosystem.

SLAB is available at: https://huggingface.co/datasets/argilla/SLAB. 

If you would like to collaborate on building additional Spanish LLM benchmarks, let's discuss in the comments.

🔗 SLAB Blog Post: https://argilla.com/blog/slab
----------
Hello everyone,

I'm thrilled to announce the release of 

https://huggingface.co/01-AI/01AI-GPT-4o -

A new family of models that brings the power of transformer AI to the masses.

This model is designed to be accessible and easy to use, while still offering high-quality results.

Key features:
- Small model size: only 23M parameters
- Supports text generation, image generation, and text-to-image tasks
- Data-efficient training with a lightweight tokenizer
- Optimized for efficient on-device usage
- Uses the powerful transformer architecture to deliver high-quality results

Excited to see what you all think!

https://huggingface.co/01-AI/01AI-GPT-4o
🚀
Saleh7 bfuzzy1 Clausss xi0v MihaiHuggingFace takeraparterer Svngoku nyuuzyou
👀
John6666 takeraparterer Clausss xi0v raincandy-u Svngoku
https://cdn-avatars.huggingface.co/v1/production/uploads/657eb5b256c9c67605a6e8b5/RPblnGJX57oiIcASEz_S8.png
raincandy_U
raincandy-u
user
https://cdn-avatars.huggingface.co/v1/production/uploads/6316fb937b0ee0136e5f1220/poHBoJ7QAF_s2CCaosdvQ.jpeg
Firstname Lastname
takeraparterer
user
https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/cA64Ix1vh75C7HoClUBhx.png
Richard A Aragon
TuringsSolutions
user