Explain GPU usage for model training
Determine GPU requirements for large language models
Upload a machine learning model to Hugging Face Hub
Create and manage ML pipelines with ZenML Dashboard
Measure over-refusal in LLMs using OR-Bench
Compare code model performance on benchmarks
Submit deepfake detection models for evaluation
Launch web-based model application
Convert Stable Diffusion checkpoint to Diffusers and open a PR
Find recent high-liked Hugging Face models
Find and download models from Hugging Face
Download a TriplaneGaussian model checkpoint
Compare model weights and visualize differences
LLM Conf talk is a model benchmarking tool designed to help users understand and optimize GPU usage during the training of large language models (LLMs). It provides detailed insights into hardware utilization, enabling more efficient model training and resource management.
1. What models does LLM Conf talk support?
LLM Conf talk is compatible with most popular LLM architectures, including but not limited to GPT, BERT, and T5.
2. Can I use LLM Conf talk for real-time monitoring?
Yes, LLM Conf talk offers real-time GPU usage monitoring, making it ideal for live training sessions.
3. Is LLM Conf talk free to use?
LLM Conf talk is currently available as an open-source tool, making it free for use and modification.