Linking pages
- GitHub - jphall663/awesome-machine-learning-interpretability: A curated list of awesome machine learning interpretability resources. https://github.com/jphall663/awesome-machine-learning-interpretability 0 comments
- Applying massive language models in the real world with Cohere – Jay Alammar – Visualizing machine learning one concept at a time. http://jalammar.github.io/applying-large-language-models-cohere/ 0 comments
- Interfaces for Explaining Transformer Language Models – Jay Alammar – Visualizing machine learning one concept at a time. https://jalammar.github.io/explaining-transformers/ 0 comments
- GitHub - ml-tooling/best-of-ml-python: 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly. https://github.com/ml-tooling/best-of-ml-python 0 comments
Linked pages
- PyTorch http://pytorch.org/ 100 comments
- GitHub - huggingface/transformers: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. https://github.com/huggingface/transformers 26 comments
- Finding the Words to Say: Hidden State Visualizations for Language Models – Jay Alammar – Visualizing machine learning one concept at a time. https://jalammar.github.io/hidden-states/ 4 comments
- interpreting GPT: the logit lens — LessWrong https://www.lesswrong.com/posts/AcKRB8wDpdaN6v6ru/interpreting-gpt-the-logit-lens 4 comments
- Interfaces for Explaining Transformer Language Models – Jay Alammar – Visualizing machine learning one concept at a time. https://jalammar.github.io/explaining-transformers/ 0 comments
- Captum · Model Interpretability for PyTorch https://captum.ai/ 0 comments
- [1905.00414] Similarity of Neural Network Representations Revisited https://arxiv.org/abs/1905.00414 0 comments
- http://arxiv.org/abs/1311.2901 0 comments
- [1312.6034] Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps https://arxiv.org/abs/1312.6034 0 comments