1.12 GB | 29min 11s | mp4 | 1280X720  | 16:9
Genre:eLearning |Language:English

Files Included :
FileName :appendix A  A typical training loop.mp4 | Size:  (15.82 MB)
FileName :appendix A  Automatic differentiation made easy.mp4 | Size:  (9.6 MB)
FileName :appendix A  Implementing multilayer neural networks.mp4 | Size:  (19.79 MB)
FileName :appendix A  Introduction to PyTorch.mp4 | Size:  (31.05 MB)
FileName :appendix A  Optimizing training performance with GPUs.mp4 | Size:  (40.3 MB)
FileName :appendix A  Saving and loading models.mp4 | Size:  (3.6 MB)
FileName :appendix A  Seeing models as computation graphs.mp4 | Size:  (4.91 MB)
FileName :appendix A  Setting up efficient data loaders.mp4 | Size:  (19.69 MB)
FileName :appendix A  Summary.mp4 | Size:  (4.82 MB)
FileName :appendix A  Understanding tensors.mp4 | Size:  (16.53 MB)
FileName :appendix D   The modified training function.mp4 | Size:  (4.06 MB)
FileName :appendix D  Adding bells and whistles to the training loop.mp4 | Size:  (7.01 MB)
FileName :appendix D  Cosine decay.mp4 | Size:  (3.9 MB)
FileName :appendix D  Gradient clipping.mp4 | Size:  (5.8 MB)
FileName :appendix E  Initializing the model.mp4 | Size:  (3.21 MB)
FileName :appendix E  Parameter-efficient fine-tuning with LoRA.mp4 | Size:  (19.63 MB)
FileName :appendix E  Parameter-efficient fine-tuning with LoRA.mp4 | Size:  (9.13 MB)
FileName :appendix E  Preparing the dataset.mp4 | Size:  (3.59 MB)
FileName :Chapter 1  A closer look at the GPT architecture.mp4 | Size:  (13.51 MB)
FileName :Chapter 1  Applications of LLMs.mp4 | Size:  (5.61 MB)
FileName :Chapter 1  Building a large language model.mp4 | Size:  (4.16 MB)
FileName :Chapter 1  Introducing the transformer architecture.mp4 | Size:  (19.04 MB)
FileName :Chapter 1  Stages of building and using LLMs.mp4 | Size:  (13.08 MB)
FileName :Chapter 1  Summary.mp4 | Size:  (3.78 MB)
FileName :Chapter 1  Understanding large language models.mp4 | Size:  (23.72 MB)
FileName :Chapter 1  Utilizing large datasets.mp4 | Size:  (9.93 MB)
FileName :Chapter 2  Adding special context tokens.mp4 | Size:  (14.58 MB)
FileName :Chapter 2  Byte pair encoding.mp4 | Size:  (9.25 MB)
FileName :Chapter 2  Converting tokens into token IDs.mp4 | Size:  (11.8 MB)
FileName :Chapter 2  Creating token embeddings.mp4 | Size:  (9.77 MB)
FileName :Chapter 2  Data sampling with a sliding window.mp4 | Size:  (19.78 MB)
FileName :Chapter 2  Encoding word positions.mp4 | Size:  (13.74 MB)
FileName :Chapter 2  Summary.mp4 | Size:  (6.68 MB)
FileName :Chapter 2  Tokenizing text.mp4 | Size:  (11.44 MB)
FileName :Chapter 2  Working with text data.mp4 | Size:  (19.24 MB)
FileName :Chapter 3  Attending to different parts of the input with self-attention.mp4 | Size:  (34.27 MB)
FileName :Chapter 3  Capturing data dependencies with attention mechanisms.mp4 | Size:  (6.73 MB)
FileName :Chapter 3  Coding attention mechanisms.mp4 | Size:  (14.21 MB)
FileName :Chapter 3  Extending single-head attention to multi-head attention.mp4 | Size:  (34.82 MB)
FileName :Chapter 3  Hiding future words with causal attention.mp4 | Size:  (30.17 MB)
FileName :Chapter 3  Implementing self-attention with trainable weights.mp4 | Size:  (38.68 MB)
FileName :Chapter 3  Summary.mp4 | Size:  (6.16 MB)
FileName :Chapter 4  Adding shortcut connections.mp4 | Size:  (12.63 MB)
FileName :Chapter 4  Coding the GPT model.mp4 | Size:  (20.76 MB)
FileName :Chapter 4  Connecting attention and linear layers in a transformer block.mp4 | Size:  (14.7 MB)
FileName :Chapter 4  Generating text.mp4 | Size:  (22.3 MB)
FileName :Chapter 4  Implementing a feed forward network with GELU activations.mp4 | Size:  (16.93 MB)
FileName :Chapter 4  Implementing a GPT model from scratch to generate text.mp4 | Size:  (29.12 MB)
FileName :Chapter 4  Normalizing activations with layer normalization.mp4 | Size:  (29 MB)
FileName :Chapter 4  Summary.mp4 | Size:  (5.34 MB)
FileName :Chapter 5  Decoding strategies to control randomness.mp4 | Size:  (30.21 MB)
FileName :Chapter 5  Loading and saving model weights in PyTorch.mp4 | Size:  (8.01 MB)
FileName :Chapter 5  Loading pretrained weights from OpenAI.mp4 | Size:  (24.8 MB)
FileName :Chapter 5  Pretraining on unlabeled data.mp4 | Size:  (69.28 MB)
FileName :Chapter 5  Summary.mp4 | Size:  (4.37 MB)
FileName :Chapter 5  Training an LLM.mp4 | Size:  (21.16 MB)
FileName :Chapter 6  Adding a classification head.mp4 | Size:  (21.23 MB)
FileName :Chapter 6  Calculating the classification loss and accuracy.mp4 | Size:  (11.53 MB)
FileName :Chapter 6  Creating data loaders.mp4 | Size:  (15.35 MB)
FileName :Chapter 6  Fine-tuning for classification.mp4 | Size:  (10.8 MB)
FileName :Chapter 6  Fine-tuning the model on supervised data.mp4 | Size:  (14.9 MB)
FileName :Chapter 6  Initializing a model with pretrained weights.mp4 | Size:  (5.63 MB)
FileName :Chapter 6  Preparing the dataset.mp4 | Size:  (9.1 MB)
FileName :Chapter 6  Summary.mp4 | Size:  (524.12 KB)
FileName :Chapter 6  Using the LLM as a spam classifier.mp4 | Size:  (3.86 MB)
FileName :Chapter 7  Conclusions.mp4 | Size:  (8.72 MB)
FileName :Chapter 7  Creating data loaders for an instruction dataset.mp4 | Size:  (10.27 MB)
FileName :Chapter 7  Evaluating the fine-tuned LLM.mp4 | Size:  (25.71 MB)
FileName :Chapter 7  Extracting and saving responses.mp4 | Size:  (14.85 MB)
FileName :Chapter 7  Fine-tuning the LLM on instruction data.mp4 | Size:  (16.57 MB)
FileName :Chapter 7  Fine-tuning to follow instructions.mp4 | Size:  (8.16 MB)
FileName :Chapter 7  Loading a pretrained LLM.mp4 | Size:  (9.84 MB)
FileName :Chapter 7  Organizing data into training batches.mp4 | Size:  (34.17 MB)
FileName :Chapter 7  Preparing a dataset for supervised instruction fine-tuning.mp4 | Size:  (11.97 MB)
FileName :Chapter 7  Summary.mp4 | Size:  (4.41 MB)]
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