Pre-trained LMs ES
Collection
Monolingual language models pre-trained on Spanish and related languages.
•
21 items
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Updated
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6
SomosNLP
non-profit
AI & ML interests
Democratizar el PLN en español e incentivar su aplicación para generar impacto social 💛
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somosnlp's activity
mariagrandury
updated
2
collections
about 17 hours ago
nataliaElv
posted
an
update
13 days ago
Post
1425
New chapter in the Hugging Face NLP course! 🤗 🚀
We've added a new chapter about the very basics of Argilla to the Hugging Face NLP course. Learn how to set up an Argilla instance, load & annotate datasets, and export them to the Hub.
Any feedback for improvements welcome!
https://huggingface.co/learn/nlp-course/chapter10
We've added a new chapter about the very basics of Argilla to the Hugging Face NLP course. Learn how to set up an Argilla instance, load & annotate datasets, and export them to the Hub.
Any feedback for improvements welcome!
https://huggingface.co/learn/nlp-course/chapter10
nataliaElv
posted
an
update
21 days ago
Post
544
Do you want to easily save annotations to a Dataset in the Hub?
In the last version of Argilla (v2.6.0), you can export your data directly from the UI to the Hub.
Check all the changes and update to the latest version: https://github.com/argilla-io/argilla/releases/tag/v2.6.0
In the last version of Argilla (v2.6.0), you can export your data directly from the UI to the Hub.
Check all the changes and update to the latest version: https://github.com/argilla-io/argilla/releases/tag/v2.6.0
nataliaElv
posted
an
update
about 1 month ago
Post
1664
If you are still wondering how the FineWeb2 annotations are done, how to follow the guidelines or how Argilla works, this is your video!
I go through a few samples of the FineWeb2 dataset and classify them based on their educational content. Check it out!
https://www.youtube.com/watch?v=_-ORB4WAVGU
I go through a few samples of the FineWeb2 dataset and classify them based on their educational content. Check it out!
https://www.youtube.com/watch?v=_-ORB4WAVGU
nataliaElv
posted
an
update
about 2 months ago
Post
1294
How do your annotations for FineWeb2 compare to your teammates'?
I started contributing some annotations to the FineWeb2 collaborative annotation sprint and I wanted to know if my labelling trends were similar to those of my teammates.
I did some analysis and I wasn't surprised to see that I'm being a bit harsher on my evaluations than my mates 😂
Do you want to see how your annotations compare to others?
👉 Go to this Gradio space: nataliaElv/fineweb2_compare_my_annotations
✍️ Enter the dataset that you've contributed to and your Hugging Face username.
How were your results?
- Contribute some annotations: data-is-better-together/fineweb-c
- Join your language channel in Rocket chat: HuggingFaceFW/discussion
I started contributing some annotations to the FineWeb2 collaborative annotation sprint and I wanted to know if my labelling trends were similar to those of my teammates.
I did some analysis and I wasn't surprised to see that I'm being a bit harsher on my evaluations than my mates 😂
Do you want to see how your annotations compare to others?
👉 Go to this Gradio space: nataliaElv/fineweb2_compare_my_annotations
✍️ Enter the dataset that you've contributed to and your Hugging Face username.
How were your results?
- Contribute some annotations: data-is-better-together/fineweb-c
- Join your language channel in Rocket chat: HuggingFaceFW/discussion
nataliaElv
posted
an
update
about 2 months ago
Post
1188
We're so close to reaching 100 languages! Can you help us cover the remaining 200? Check if we're still looking for language leads for your language:
nataliaElv/language-leads-dashboard
Post
535
🌐 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.
frascuchon
posted
an
update
2 months ago
Post
394
🚀 Argilla v2.5.0 is out! 🎉
We’re excited to announce the latest version of Argilla, packed with features to make your data annotation workflows more powerful and seamless. Here’s what’s new:
✨ 1. Argilla Webhooks
With Argilla webhooks, you can:
* Trigger custom workflows
* Seamlessly integrate with external tools
* Build custom event-driven pipelines
🐍 2. Support for Python 3.13 and Pydantic v2
Argilla v2.5.0 now runs on:
* Python 3.13 for enhanced compatibility and speed
* Pydantic v2 for improved performance and type validation
🎨 3. Redesigned Home Page
Argilla's home page has been redesigned to provide a better user experience, showing a new dataset card view, which provides a better overview of the datasets and annotation progress.
📖 Read the full release notes 👉 https://github.com/argilla-io/argilla/releases/tag/v2.5.0)
⬇️ Update now 👉 https://pypi.org/project/argilla)
or use the live demo 👉 argilla/argilla-template-space
We’re excited to announce the latest version of Argilla, packed with features to make your data annotation workflows more powerful and seamless. Here’s what’s new:
✨ 1. Argilla Webhooks
With Argilla webhooks, you can:
* Trigger custom workflows
* Seamlessly integrate with external tools
* Build custom event-driven pipelines
🐍 2. Support for Python 3.13 and Pydantic v2
Argilla v2.5.0 now runs on:
* Python 3.13 for enhanced compatibility and speed
* Pydantic v2 for improved performance and type validation
🎨 3. Redesigned Home Page
Argilla's home page has been redesigned to provide a better user experience, showing a new dataset card view, which provides a better overview of the datasets and annotation progress.
📖 Read the full release notes 👉 https://github.com/argilla-io/argilla/releases/tag/v2.5.0)
⬇️ Update now 👉 https://pypi.org/project/argilla)
or use the live demo 👉 argilla/argilla-template-space
nataliaElv
posted
an
update
2 months ago
Post
1643
Would you like to get a high-quality dataset to pre-train LLMs in your language? 🌏
At Hugging Face we're preparing a collaborative annotation effort to build an open-source multilingual dataset as part of the Data is Better Together initiative.
Follow the link below, check if your language is listed and sign up to be a Language Lead!
https://forms.gle/s9nGajBh6Pb9G72J6
At Hugging Face we're preparing a collaborative annotation effort to build an open-source multilingual dataset as part of the Data is Better Together initiative.
Follow the link below, check if your language is listed and sign up to be a Language Lead!
https://forms.gle/s9nGajBh6Pb9G72J6
nataliaElv
posted
an
update
2 months ago
Post
366
You can now add your Bluesky handle to your Hugging Face profile! 🦋
Have you noticed?
Have you noticed?
Post
788
🤖💻 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.
mariagrandury
updated
a
collection
2 months ago
Post
2277
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
2520
Spent the weekend testing out some prompts with 🕵️♂️Mystery Bot🕵️♂️ on my mobile... exciting things are coming soon for the following languages:
🌐Arabic, Chinese, Czech, Dutch, English French, German, Greek, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese!🌐
🌐Arabic, Chinese, Czech, Dutch, English French, German, Greek, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese!🌐
Post
408
Take a look at distilabel's last blog post to see how to leverage FinePersonas to create AI users for a social network, inspired by SocialAI's app: https://x.com/michaelsayman/status/1835841675584811239
- Link: https://distilabel.argilla.io/dev/sections/pipeline_samples/examples/fine_personas_social_network/
- Sample dataset: plaguss/FinePersonas-SocialAI-test
- FinePersonas: argilla/FinePersonas-v0.1
- Link: https://distilabel.argilla.io/dev/sections/pipeline_samples/examples/fine_personas_social_network/
- Sample dataset: plaguss/FinePersonas-SocialAI-test
- FinePersonas: argilla/FinePersonas-v0.1
Post
1391
📢 2024 CVPR Videos Are Now Available! 🎥
CVPR conference keynotes, panels, posters, workshops, and other content are now available.
⬇️
https://cvpr.thecvf.com/Conferences/2024/Videos
CVPR conference keynotes, panels, posters, workshops, and other content are now available.
⬇️
https://cvpr.thecvf.com/Conferences/2024/Videos
gabrielmbmb
posted
an
update
5 months ago
Post
1846
Yesterday
@mattshumer
released
mattshumer/Reflection-Llama-3.1-70B, an impressive model that achieved incredible results in benchmarks like MMLU. The model was fine-tuned using Reflection-Tuning and the dataset used wasn't released, but I created a small recipe with distilabel that allows generating a dataset with a similar output format:
1. We use MagPie 🐦 in combination with https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct to generate reasoning instructions.
2. We generate a response again using https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct, but we steer the LLM to generate an specific output format using a custom system prompt. In the system prompt, we instruct the LLM that it will have first to think 💭 and have reflections that will help resolving ambiguities. After that, we instruct the LLM to generate an output based on the previous thinking
In this dataset gabrielmbmb/distilabel-reflection-tuning you can found 5 rows that I generated with this recipe. You can also found the code of the pipeline in the file called
1. We use MagPie 🐦 in combination with https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct to generate reasoning instructions.
2. We generate a response again using https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct, but we steer the LLM to generate an specific output format using a custom system prompt. In the system prompt, we instruct the LLM that it will have first to think 💭 and have reflections that will help resolving ambiguities. After that, we instruct the LLM to generate an output based on the previous thinking
In this dataset gabrielmbmb/distilabel-reflection-tuning you can found 5 rows that I generated with this recipe. You can also found the code of the pipeline in the file called
reflection.py.Post
2351
💡Andrew Ng recently gave a strong defense of Open Source AI models and the need to slow down legislative efforts in the US and the EU to restrict innovation in Open Source AI at Stanford GSB.
🎥See video below
https://youtu.be/yzUdmwlh1sQ?si=bZc690p8iubolXm_
🎥See video below
https://youtu.be/yzUdmwlh1sQ?si=bZc690p8iubolXm_
- 4 replies
daqc
updated
a
model
5 months ago