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albertvillanova 
posted an update about 1 month ago
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2292
🚀 TRL v0.29.0 introduces trl-training: an agent-native training skill.

This makes the TRL CLI a structured, agent-readable capability, allowing AI agents to reliably execute training workflows such as:
- Supervised Fine-Tuning (SFT)
- Direct Preference Optimization (DPO)
- Group Relative Policy Optimization (GRPO)

We’re excited to see what the community builds on top of this.

If you’re working on AI agents, alignment research, or scalable RL training infrastructure: give TRL v0.29.0 a try! 🤗

The future of ML tooling is agent-native.
🔗 https://github.com/huggingface/trl/releases/tag/v0.29.0
albertvillanova 
posted an update about 2 months ago
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1835
5 years already working in democratizing AI 🤗
Grateful to be part of such an awesome team making it happen every day.
MaximumEntropy 
authored a paper 3 months ago
woojun-jung 
authored a paper 4 months ago
Teja-Gollapudi 
authored a paper 6 months ago
Teja-Gollapudi 
authored 2 papers 7 months ago
albertvillanova 
posted an update 8 months ago
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4611
Latest smolagents release supports GPT-5: build agents that think, plan, and act.
⚡ Upgrade now and put GPT-5 to work!
  • 1 reply
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albertvillanova 
posted an update 8 months ago
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708
🚀 smolagents v1.21.0 is here!
Now with improved safety in the local Python executor: dunder calls are blocked!
⚠️ Still, not fully isolated: for untrusted code, use a remote executor instead: Docker, E2B, Wasm.
✨ Many bug fixes: more reliable code.
👉 https://github.com/huggingface/smolagents/releases/tag/v1.21.0
merterbak 
posted an update 8 months ago
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5095
OpenAI is now open again! Check out OpenAI’s brand new gpt‑oss‑20b model hosted on ZeroGPU 🤗

merterbak/gpt-oss-20b-demo
AtAndDev 
posted an update 9 months ago
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665
Qwen 3 Coder is a personal attack to k2, and I love it.
It achieves near SOTA on LCB while not having reasoning.
Finally people are understanding that reasoning isnt necessary for high benches...

Qwen ftw!

DECENTRALIZE DECENTRALIZE DECENTRALIZE
albertvillanova 
posted an update 9 months ago
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826
🚀 New in smolagents v1.20.0: Remote Python Execution via WebAssembly (Wasm)

We've just merged a major new capability into the smolagents framework: the CodeAgent can now execute Python code remotely in a secure, sandboxed WebAssembly environment!

🔧 Powered by Pyodide and Deno, this new WasmExecutor lets your agent-generated Python code run safely: without relying on Docker or local execution.

Why this matters:
✅ Isolated execution = no host access
✅ No need for Python on the user's machine
✅ Safer evaluation of arbitrary code
✅ Compatible with serverless / edge agent workloads
✅ Ideal for constrained or untrusted environments

This is just the beginning: a focused initial implementation with known limitations. A solid MVP designed for secure, sandboxed use cases. 💡

💡 We're inviting the open-source community to help evolve this executor:
• Tackle more advanced Python features
• Expand compatibility
• Add test coverage
• Shape the next-gen secure agent runtime

🔗 Check out the PR: https://github.com/huggingface/smolagents/pull/1261

Let's reimagine what agent-driven Python execution can look like: remote-first, wasm-secure, and community-built.

This feature is live in smolagents v1.20.0!
Try it out.
Break things. Extend it. Give us feedback.
Let's build safer, smarter agents; together 🧠⚙️

👉 https://github.com/huggingface/smolagents/releases/tag/v1.20.0

#smolagents #WebAssembly #Python #AIagents #Pyodide #Deno #OpenSource #HuggingFace #AgenticAI
albertvillanova 
posted an update 10 months ago
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1845
🚀 SmolAgents v1.19.0 is live!
This release brings major improvements to agent flexibility, UI usability, streaming architecture, and developer experience: making it easier than ever to build smart, interactive AI agents. Here's what's new:

🔧 Agent Upgrades
- Support for managed agents in ToolCallingAgent
- Context manager support for cleaner agent lifecycle handling
- Output formatting now uses XML tags for consistency

🖥️ UI Enhancements
- GradioUI now supports reset_agent_memory: perfect for fresh starts in dev & demos.

🔄 Streaming Refactor
- Streaming event aggregation moved off the Model class
- ➡️ Better architecture & maintainability

📦 Output Tracking
- CodeAgent outputs are now stored in ActionStep
- ✅ More visibility and structure to agent decisions

🐛 Bug Fixes
- Smarter planning logic
- Cleaner Docker logs
- Better prompt formatting for additional_args
- Safer internal functions and final answer matching

📚 Docs Improvements
- Added quickstart examples with tool usage
- One-click Colab launch buttons
- Expanded reference docs (AgentMemory, GradioUI docstrings)
- Fixed broken links and migrated to .md format

🔗 Full release notes:
https://github.com/huggingface/smolagents/releases/tag/v1.19.0

💬 Try it out, explore the new features, and let us know what you build!

#smolagents #opensource #AIagents #LLM #HuggingFace
AtAndDev 
posted an update 11 months ago
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3139
deepseek-ai/DeepSeek-R1-0528

This is the end
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albertvillanova 
posted an update 11 months ago
albertvillanova 
posted an update 11 months ago
merterbak 
posted an update 11 months ago
merterbak 
posted an update 11 months ago
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2659
Seed-Coder released and it's designed for coding tasks, featuring base, instruct, and reasoning variants at an 8B parameter scale developed by ByteDance Seed team. Unlike traditional open source LLMs that rely on human crafted rules or annotated data for curating code pretraining datasets Seed-Coder introduces a model-centric data pipeline. The pipeline processes raw data from GitHub and web archives into four categories: file-level codes, repository-level codes, GitHub commits, and code-related web data.A quality filter LLM, evaluates code (for readability, modularity, clarity, and reusability) by removing the lowest 10% to create a 6 trillion token dataset supporting 89 programming languages.
Models: ByteDance-Seed/seed-coder-680de32c15ead6555c75b0e4
Github: https://github.com/ByteDance-Seed/Seed-Coder/tree/master
Paper: https://github.com/ByteDance-Seed/Seed-Coder/blob/master/Seed-Coder.pdf
merterbak 
posted an update 11 months ago
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1726
Microsoft released their new fine-tuned phi-4 models with reasoning data yesterday. They outperform/rival much larger models . Check out them if you haven't yet. 🚀

Phi4 mini reasoning(SFT): microsoft/Phi-4-mini-reasoning
Phi-4 reasoning(SFT): microsoft/Phi-4-reasoning
Phi-4 reasoning plus (SFT + RL): microsoft/Phi-4-reasoning-plus
Demo: https://github.com/marketplace/models/azureml/Phi-4-reasoning/playground
Articles: https://arxiv.org/pdf/2504.21318
https://arxiv.org/pdf/2504.21233
Blog: https://azure.microsoft.com/en-us/blog/one-year-of-phi-small-language-models-making-big-leaps-in-ai/

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merterbak 
posted an update 12 months ago
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5104
Qwen 3 models released🔥
It offers 2 MoE and 6 dense models with following parameter sizes: 0.6B, 1.7B, 4B, 8B, 14B, 30B(MoE), 32B, and 235B(MoE).
Models: Qwen/qwen3-67dd247413f0e2e4f653967f
Blog: https://qwenlm.github.io/blog/qwen3/
Demo: Qwen/Qwen3-Demo
GitHub: https://github.com/QwenLM/Qwen3

✅ Pre-trained 119 languages(36 trillion tokens) and dialects with strong translation and instruction following abilities. (Qwen2.5 was pre-trained on 18 trillion tokens.)
✅Qwen3 dense models match the performance of larger Qwen2.5 models. For example, Qwen3-1.7B/4B/8B/14B/32B perform like Qwen2.5-3B/7B/14B/32B/72B.
✅ Three stage done while pretraining:
• Stage 1: General language learning and knowledge building.
• Stage 2: Reasoning boost with STEM, coding, and logic skills.
• Stage 3: Long context training
✅ It supports MCP in the model
✅ Strong agent skills
✅ Supports seamless between thinking mode (for hard tasks like math and coding) and non-thinking mode (for fast chatting) inside chat template.
✅ Better human alignment for creative writing, roleplay, multi-turn conversations, and following detailed instructions.