Building Moon Bot: A Slack-Native Coding Agent Backed by HuggingFace Buckets
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Seeing the Needle in the Haystack: Towards Weakly-Supervised Log Instance Anomaly Localization via Counterfactual Perturbation
Qualixar OS: A Universal Operating System for AI Agent Orchestration
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nielsr
updated a
Space about 1 hour ago
tarekziade
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bucket about 13 hours ago
alvarobartt
updated a
dataset about 13 hours ago
evalstate
updated a
bucket 1 day ago
lysandre
updated a
dataset 1 day ago
sergiopaniego
posted an update 2 days ago
Post
78
you can now train your own coding agents with trl + openenv, starting with opencode
we just added end-to-end support for training agent harnesses:
> TRL: a loop-owning training path (AsyncGRPOTrainer + HarnessRolloutWorker) that launches the agent in an OpenEnv session, reads back its trace, reconstructs the training samples, and trains with AsyncGRPO
> OpenEnv: the OpenCode harness environment plus a transparent proxy that forwards the agent's model calls and records each turn's token ids and logprobs
you train the actual opencode agent as is, it runs its own loop and tools and the policy learns from the exact tokens it produced
we're shipping a self-contained example: local subprocess sandbox, DeepCoder problems, validated on Qwen3-8B.
> example: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/opencode.py
> docs: https://huggingface.co/docs/trl/main/openenv
and we're working actively on both sides so expect more 🤓
we just added end-to-end support for training agent harnesses:
> TRL: a loop-owning training path (AsyncGRPOTrainer + HarnessRolloutWorker) that launches the agent in an OpenEnv session, reads back its trace, reconstructs the training samples, and trains with AsyncGRPO
> OpenEnv: the OpenCode harness environment plus a transparent proxy that forwards the agent's model calls and records each turn's token ids and logprobs
you train the actual opencode agent as is, it runs its own loop and tools and the policy learns from the exact tokens it produced
we're shipping a self-contained example: local subprocess sandbox, DeepCoder problems, validated on Qwen3-8B.
> example: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/opencode.py
> docs: https://huggingface.co/docs/trl/main/openenv
and we're working actively on both sides so expect more 🤓
- 1 reply
sergiopaniego
posted an update 3 days ago
Post
1404
you can train DiffusionGemma (a block-diffusion LLM) in TRL! and we're sharing an example for it
TRL trainers are made to be easily extended and adapted to different real-world use cases.
in this one, with a single method overridden in SFTTrainer (compute_loss), you can train this model
> example: https://github.com/huggingface/trl/blob/main/examples/scripts/sft_diffusion_gemma.py
TRL trainers are made to be easily extended and adapted to different real-world use cases.
in this one, with a single method overridden in SFTTrainer (compute_loss), you can train this model
> example: https://github.com/huggingface/trl/blob/main/examples/scripts/sft_diffusion_gemma.py
sergiopaniego
posted an update 4 days ago
Post
150
join us next Tuesday, July 28, for Class 3 of the Training Agents live series!
we'll dive into reinforcement learning for agent training, covering the intuition behind GRPO, how it works, and how to implement it in TRL with practical, e2e examples
see you there 🤠
live: https://www.youtube.com/live/ztdTed5egrM
> in case you missed class 1:
https://x.com/SergioPaniego/status/2069382207618379813
> and in case you missed class 2: https://x.com/SergioPaniego/status/2075180665184686187
we'll dive into reinforcement learning for agent training, covering the intuition behind GRPO, how it works, and how to implement it in TRL with practical, e2e examples
see you there 🤠
live: https://www.youtube.com/live/ztdTed5egrM
> in case you missed class 1:
https://x.com/SergioPaniego/status/2069382207618379813
> and in case you missed class 2: https://x.com/SergioPaniego/status/2075180665184686187
sayakpaul
authored a
paper 6 days ago
nielsr
submitted a
paper to Daily Papers 11 days ago
nielsr
submitted a
paper to Daily Papers 12 days ago
Post
1281
Hugging Face MCP Server v0.3.29
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Included "papers" in the new hf_fs tool. Includes listing of trending/daily.
This is a new tool under observation - disable the "Paper Semantic Search" tool for best results.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Included "papers" in the new hf_fs tool. Includes listing of trending/daily.
This is a new tool under observation - disable the "Paper Semantic Search" tool for best results.
hf://papers/
├── README.md
├── daily/
│ ├── latest
│ └── YYYY/
│ └── MM/
│ └── DD/
├── trending/
└── ARXIV_ID/
├── metadata.json
├── paper.md
├── models/
├── datasets/
└── spaces/sayakpaul
authored 3
papers 16 days ago
sayakpaul
submitted a
paper to Daily Papers 16 days ago
nielsr
submitted 2
papers to Daily Papers 17 days ago
sergiopaniego
posted an update 18 days ago
Post
7692
Frontier models use distillation as a step of their post-training pipelines.
In 2026 it has three jobs: compress a big model into a small one, merge RL experts into a single model, and let a model teach itself.
I wrote up which frontier models use each one and how: https://huggingface.co/blog/sergiopaniego/distillation-2026
It pairs with Class 2 of the Training an Agent series Ben and I are doing, where we teach these techniques hands-on with TRL!
In 2026 it has three jobs: compress a big model into a small one, merge RL experts into a single model, and let a model teach itself.
I wrote up which frontier models use each one and how: https://huggingface.co/blog/sergiopaniego/distillation-2026
It pairs with Class 2 of the Training an Agent series Ben and I are doing, where we teach these techniques hands-on with TRL!
- 3 replies
nielsr
submitted a
paper to Daily Papers 18 days ago