rednote-hilab/dots.llm1.inst
Text Generation
•
Updated
•
23
•
60
Djuunaa
djuna
AI & ML interests
None yet
Recent Activity
liked
a model
about 8 hours ago
rednote-hilab/dots.llm1.inst
new activity
about 8 hours ago
rednote-hilab/dots.llm1.inst:Game-changer for 4x24GB setups! AWQ request
liked
a model
about 17 hours ago
Gen-Verse/ReasonFlux-Coder-14B
Organizations
djuna's activity
liked
a
model
about 8 hours ago
Game-changer for 4x24GB setups! AWQ request
1
#1 opened about 9 hours ago
by
hyunw55
liked
2
models
about 17 hours ago
reacted to
MJannik's
post with 🤝
about 17 hours ago
Post
1378
Hi everyone, we’ve got big news! Starting today, all Langfuse product features are available as free OSS (MIT license).
You can now upgrade your self-hosted Langfuse to access features like:
- Managed LLM-as-a-Judge evaluations
- Annotation queues
- Prompt experiments
- LLM playground
We’re incredibly grateful for the support of this amazing community and can’t wait to hear your feedback on the new features!
More on this change here: https://langfuse.com/blog/2025-06-04-open-sourcing-langfuse-product
You can now upgrade your self-hosted Langfuse to access features like:
- Managed LLM-as-a-Judge evaluations
- Annotation queues
- Prompt experiments
- LLM playground
We’re incredibly grateful for the support of this amazing community and can’t wait to hear your feedback on the new features!
More on this change here: https://langfuse.com/blog/2025-06-04-open-sourcing-langfuse-product
liked
a
model
about 18 hours ago
liked
a
model
2 days ago
reacted to
eaddario's
post with 🚀
2 days ago
Post
1231
Layer-wise and Pruned versions of google/gemma-3-12b-it
After enhancing llama.cpp to handle user-defined quantization levels for arbitrary tensors (https://github.com/ggml-org/llama.cpp/pull/12511), I have added an option to prune whole layers (https://github.com/ggml-org/llama.cpp/pull/13037), and have published two versions of google/gemma-3-12b-it for demo and testing purposes:
* Tesor-wise: eaddario/gemma-3-12b-it-GGUF
* Pruned: eaddario/gemma-3-12b-it-pruned-GGUF
Even though the Perplexity scores of the pruned version are 3 times higher, the ARC, HellaSwag, MMLU, Truthful QA and WinoGrande scores are holding remarkably well, considering two layers were removed (26 and 29). This seems to support Xin Men et al conclusions in ShortGPT: Layers in Large Language Models are More Redundant Than You Expect (2403.03853)
Results summary in the model's card and test results in the ./scores directory. Questions/feedback is always welcomed.
After enhancing llama.cpp to handle user-defined quantization levels for arbitrary tensors (https://github.com/ggml-org/llama.cpp/pull/12511), I have added an option to prune whole layers (https://github.com/ggml-org/llama.cpp/pull/13037), and have published two versions of google/gemma-3-12b-it for demo and testing purposes:
* Tesor-wise: eaddario/gemma-3-12b-it-GGUF
* Pruned: eaddario/gemma-3-12b-it-pruned-GGUF
Even though the Perplexity scores of the pruned version are 3 times higher, the ARC, HellaSwag, MMLU, Truthful QA and WinoGrande scores are holding remarkably well, considering two layers were removed (26 and 29). This seems to support Xin Men et al conclusions in ShortGPT: Layers in Large Language Models are More Redundant Than You Expect (2403.03853)
Results summary in the model's card and test results in the ./scores directory. Questions/feedback is always welcomed.
DeepSeek-R1-Lite
❤️
🚀
19
7
#6 opened 8 days ago
by
Dampfinchen
liked
a
model
3 days ago
liked
a
model
4 days ago
liked
a
model
6 days ago
liked
a
model
7 days ago
updated
a
model
8 days ago
liked
a
model
8 days ago
The space keeps sleeping due to inactivity
👀
1
#54 opened 8 days ago
by
djuna
published
a
model
8 days ago
Update app.py to prevent users from running multiple jobs
👍
1
3
#46 opened 3 months ago
by
Blazgo
liked
a
model
9 days ago
