Results for “stm32”
17 skills
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nvidia Nv Generate Mr Brain
Generates synthetic brain MRI volumes using NVIDIA's NV-Generate-CTMR workflow, with configurable modality and random seed.
2.2k · bundle
nvidia Mcore Run On Slurm
Launch distributed Megatron-LM training jobs on a SLURM cluster with a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules, container conventions, monitoring, and per-rank failure diagnosis.
2.2k · bundle
qcmuu Mamba Architecture
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
0 · bundle
mukul975 Implementing Cisa Zero Trust Maturity Model
Assess and implement the CISA Zero Trust Maturity Model v2.0 across identity, devices, networks, applications, and data pillars to achieve progressive zero trust maturity.
24.6k · bundle
orchestra-research Mamba Architecture
Train and run Mamba state-space models with O(n) complexity, achieving faster inference and longer context than Transformers.
10.4k · bundle
dokhacgiakhoa Network 101
This skill should be used when the user asks to "set up a web server", "configure HTTP or HTTPS", "perform SNMP enumeration", "configure SMB shares", "test network services", or needs guidance on configuring and testing network services for penetration testing labs.
505 · bundle
orchestra-research Simpo Training
Train language models with SimPO, a reference-free preference optimization method that outperforms DPO without needing a reference model.
10.4k · bundle
tianhao909 Mamba Architecture
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
1 · bundle
vimalinx Hmmstat
Use when you need to inspect and summarize statistics for HMM (profile hidden Markov model) files from the HMMER suite.
0 · bundle
aniruddhaadak80 Simpo Training
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.
0 · bundle
dvcrn Stt
Transcribes audio files to text using OpenAI Whisper, optimized for Brazilian Portuguese, with support for common audio formats and timestamped output.
32 · bundle
infometa Mcporter
Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.
228
qcmuu Simpo Training
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.
0 · bundle
lord1egypt Simpo Training
Trains LLMs with SimPO, a reference-free preference optimization method that outperforms DPO, using configurable hyperparameters and workflows for various models and tasks.
2
tianhao909 Simpo Training
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.
1 · bundle
peteedoo Simpo Training
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.
0 · bundle