argilla-internal-testing/test_import_dataset_from_hub_with_classlabel_f76cd8f5-ae63-42dd-b327-050daebc5b34
Viewer
•
Updated
•
3
argilla-internal-testing
company
AI & ML interests
Data Quality
Recent Activity
View all activity
argilla-internal-testing's activity
davidberenstein1957
updated
a
dataset
16 minutes ago
davidberenstein1957
published
a
dataset
16 minutes ago
davidberenstein1957
updated
6
datasets
16 minutes ago
argilla-internal-testing/test_import_dataset_from_hub_using_wrong_settings_with_records_False
Updated
•
359
argilla-internal-testing/test_import_dataset_from_hub_using_wrong_settings_with_records_True
Viewer
•
Updated
•
3
•
377
argilla-internal-testing/test_import_dataset_from_hub_using_settings_with_recordsFalse
Updated
•
2.41k
argilla-internal-testing/test_import_dataset_from_hub_using_settings_with_recordsTrue
Viewer
•
Updated
•
3
•
344
argilla-internal-testing/test_import_dataset_from_hub_with_records_False
Updated
•
304
argilla-internal-testing/test_import_dataset_from_hub_with_records_True
Viewer
•
Updated
•
3
•
443
davidberenstein1957
updated
2
datasets
17 minutes ago
davidberenstein1957
posted
an
update
2 days ago
Post
2693
🚀 Find banger tools for your smolagents!
I created the Tools gallery, which makes tools specifically developed by/for smolagents searchable and visible. This will help with:
- inspiration
- best practices
- finding cool tools
Space: davidberenstein1957/smolagents-and-tools
I created the Tools gallery, which makes tools specifically developed by/for smolagents searchable and visible. This will help with:
- inspiration
- best practices
- finding cool tools
Space: davidberenstein1957/smolagents-and-tools
- 1 reply
burtenshaw
posted
an
update
3 days ago
Post
8039
The Hugging Face agents course is finally out!
👉 https://huggingface.co/agents-course
This first unit of the course sets you up with all the fundamentals to become a pro in agents.
- What's an AI Agent?
- What are LLMs?
- Messages and Special Tokens
- Understanding AI Agents through the Thought-Action-Observation Cycle
- Thought, Internal Reasoning and the Re-Act Approach
- Actions, Enabling the Agent to Engage with Its Environment
- Observe, Integrating Feedback to Reflect and Adapt
👉 https://huggingface.co/agents-course
This first unit of the course sets you up with all the fundamentals to become a pro in agents.
- What's an AI Agent?
- What are LLMs?
- Messages and Special Tokens
- Understanding AI Agents through the Thought-Action-Observation Cycle
- Thought, Internal Reasoning and the Re-Act Approach
- Actions, Enabling the Agent to Engage with Its Environment
- Observe, Integrating Feedback to Reflect and Adapt
davidberenstein1957
posted
an
update
4 days ago
Post
2192
Fine-tune Deepseek-R1 with a Synthetic Reasoning Dataset
Blog: https://huggingface.co/blog/sdiazlor/fine-tune-deepseek-with-a-synthetic-reasoning-data
Blog: https://huggingface.co/blog/sdiazlor/fine-tune-deepseek-with-a-synthetic-reasoning-data
burtenshaw
posted
an
update
7 days ago
Post
3310
SmolLM2 paper is out! 😊
😍 Why do I love it? Because it facilitates teaching and learning!
Over the past few months I've engaged with (no joke) thousands of students based on SmolLM.
- People have inferred, fine-tuned, aligned, and evaluated this smol model.
- People used they're own machines and they've used free tools like colab, kaggle, and spaces.
- People tackled use cases in their job, for fun, in their own language, and with their friends.
upvote the paper SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model (2502.02737)
😍 Why do I love it? Because it facilitates teaching and learning!
Over the past few months I've engaged with (no joke) thousands of students based on SmolLM.
- People have inferred, fine-tuned, aligned, and evaluated this smol model.
- People used they're own machines and they've used free tools like colab, kaggle, and spaces.
- People tackled use cases in their job, for fun, in their own language, and with their friends.
upvote the paper SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model (2502.02737)
- 1 reply
plaguss
authored
a
paper
8 days ago
burtenshaw
authored
a
paper
8 days ago
davidberenstein1957
posted
an
update
8 days ago
Post
1916
Agentic RAG: Applied, visual, and step-by-step! 🐾
Get familiar with the Agents and tools, not the bells and whistles!
Retrieve - Augment and now GENERATE.
part 3: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-3-generate
Get familiar with the Agents and tools, not the bells and whistles!
Retrieve - Augment and now GENERATE.
part 3: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-3-generate
davidberenstein1957
posted
an
update
9 days ago
Post
2732
Anyone can create free hosted tools for their AI agents! 🔥
Agentic RAG stack part 2 - augment
Augment retrieval results by reranking optimises content without increasing time too much
part2: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-2-augment
code: https://github.com/huggingface/ai-blueprint
Agentic RAG stack part 2 - augment
Augment retrieval results by reranking optimises content without increasing time too much
part2: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-2-augment
code: https://github.com/huggingface/ai-blueprint
davidberenstein1957
posted
an
update
10 days ago
Post
1896
Creating an agentic RAG stack on the Hugging Face Hub - part 1 - retrieval (1/5).
🚀 Web apps and microservices included!
Chunk, embed and index documents at a huge scale without overhead.
Blog: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-1-retrieve
🚀 Web apps and microservices included!
Chunk, embed and index documents at a huge scale without overhead.
Blog: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-1-retrieve
davidberenstein1957
posted
an
update
15 days ago
Post
1573
tldr; Parquet is awesome, DuckDB too!
Datasets on the Hugging Face Hub rely on parquet files. We can interact with these files using DuckDB as a fast in-memory database system. One of DuckDB’s features is vector similarity search which can be used with or without an index.
blog:
https://huggingface.co/learn/cookbook/vector_search_with_hub_as_backend
Datasets on the Hugging Face Hub rely on parquet files. We can interact with these files using DuckDB as a fast in-memory database system. One of DuckDB’s features is vector similarity search which can be used with or without an index.
blog:
https://huggingface.co/learn/cookbook/vector_search_with_hub_as_backend