zai-org/GLM-5.2
Text Generation • 753B • Updated • 282k • • 3.61k
ZhangGuangyi
Muttermal
AI & ML interests
NLP
Recent Activity
liked a model 21 days ago
zai-org/GLM-5.2 liked a model about 1 month ago
deepseek-ai/DeepSeek-V4-Flash upvoted an article 3 months ago
TRL v1.0: Post-Training Library Built to Move with the FieldOrganizations
liked a
model 21 days ago
liked a
model about 1 month ago
upvoted an article 3 months ago
Article
TRL v1.0: Post-Training Library Built to Move with the Field
- +2
qgallouedec, stevhliu, pcuenq, sergiopaniego
• • 58 liked 2
models 4 months ago
liked a
model 5 months ago
liked a
dataset 5 months ago
liked 2
models 6 months ago
upvoted an article 10 months ago
Article
From GRPO to DAPO and GSPO: What, Why, and How
NormalUhr
• • 129 liked a
dataset 10 months ago
liked a
Space 10 months ago
upvoted an article 12 months ago
Article
KV Caching Explained: Optimizing Transformer Inference Efficiency
not-lain
• • 362 upvoted an article over 1 year ago
Article
SmolVLM Grows Smaller – Introducing the 256M & 500M Models!
- +1
andito, mfarre, merve
• • 192 liked a
dataset over 1 year ago
liked a
model over 1 year ago
liked a
dataset over 1 year ago
liked 2
models over 1 year ago
reacted to dvilasuero's post with 🤗 over 2 years ago
Post
🤗 Data is better together!
Data is essential for training good AI systems. We believe that the amazing community built around open machine learning can also work on developing amazing datasets together.
To explore how this can be done, Argilla and Hugging Face are thrilled to announce a collaborative project where we’re asking Hugging Face community members to build a dataset consisting of LLM prompts collectively.
What are we doing?
Using an instance of Argilla — a powerful open-source data collaboration tool — hosted on the Hugging Face Hub, we are collecting ratings of prompts based on their quality.
How Can You Contribute?
It’s super simple to start contributing:
1. Sign up if you don’t have a Hugging Face account
2. Go to this Argilla Space and sign in: https://huggingface.co/spaces/DIBT/prompt-collective
3. Read the guidelines and start rating prompts!
You can also join the #data-is-better-together channel in the Hugging Face Discord.
Finally, to track the community progress we'll be updating this Gradio dashboard:
https://huggingface.co/spaces/DIBT/prompt-collective-dashboard
Data is essential for training good AI systems. We believe that the amazing community built around open machine learning can also work on developing amazing datasets together.
To explore how this can be done, Argilla and Hugging Face are thrilled to announce a collaborative project where we’re asking Hugging Face community members to build a dataset consisting of LLM prompts collectively.
What are we doing?
Using an instance of Argilla — a powerful open-source data collaboration tool — hosted on the Hugging Face Hub, we are collecting ratings of prompts based on their quality.
How Can You Contribute?
It’s super simple to start contributing:
1. Sign up if you don’t have a Hugging Face account
2. Go to this Argilla Space and sign in: https://huggingface.co/spaces/DIBT/prompt-collective
3. Read the guidelines and start rating prompts!
You can also join the #data-is-better-together channel in the Hugging Face Discord.
Finally, to track the community progress we'll be updating this Gradio dashboard:
https://huggingface.co/spaces/DIBT/prompt-collective-dashboard
- 5 replies