[ WebToolTip.com ] Code with the Author of Build an LLM (From Scratch)

• ~Get Your Files Here !/009. Chapter 3. A simple self-attention mechanism without trainable weights Part 1.mp4-173.89 MB
• ~Get Your Files Here !/040. Chapter 6. Fine-tuning the model on supervised data.mp4-162.72 MB
• ~Get Your Files Here !/028. Chapter 5. Training an LLM.mp4-138.82 MB
• ~Get Your Files Here !/017. Chapter 3. Implementing multi-head attention with weight splits.mp4-127.05 MB
• ~Get Your Files Here !/034. Chapter 5. Loading pretrained weights from OpenAI.mp4-106.61 MB
• ~Get Your Files Here !/035. Chapter 6. Preparing the dataset.mp4-103.83 MB
• ~Get Your Files Here !/048. Chapter 7. Evaluating the fine-tuned LLM.mp4-102.12 MB
• ~Get Your Files Here !/020. Chapter 4. Implementing a feed forward network with GELU activations.mp4-102.08 MB
• ~Get Your Files Here !/002. Chapter 2. Tokenizing text.mp4-99.09 MB
• ~Get Your Files Here !/046. Chapter 7. Fine-tuning the LLM on instruction data.mp4-98.16 MB
• ~Get Your Files Here !/026. Chapter 5. Calculating the text generation loss cross entropy and perplexity.mp4-97.57 MB
• ~Get Your Files Here !/027. Chapter 5. Calculating the training and validation set losses.mp4-94.71 MB
• ~Get Your Files Here !/006. Chapter 2. Data sampling with a sliding window.mp4-91.88 MB
• ~Get Your Files Here !/001. Chapter 1. Python Environment Setup.mp4-90.23 MB
• ~Get Your Files Here !/019. Chapter 4. Normalizing activations with layer normalization.mp4-84.01 MB
• ~Get Your Files Here !/043. Chapter 7. Organizing data into training batches.mp4-79.82 MB
• ~Get Your Files Here !/038. Chapter 6. Adding a classification head.mp4-73.66 MB
• ~Get Your Files Here !/025. Chapter 5. Using GPT to generate text.mp4-71.59 MB
• ~Get Your Files Here !/005. Chapter 2. Byte pair encoding.mp4-69.7 MB
• ~Get Your Files Here !/023. Chapter 4. Coding the GPT model.mp4-66.96 MB
• ~Get Your Files Here !/024. Chapter 4. Generating text.mp4-65.74 MB
• ~Get Your Files Here !/039. Chapter 6. Calculating the classification loss and accuracy.mp4-64.48 MB
• ~Get Your Files Here !/022. Chapter 4. Connecting attention and linear layers in a transformer block.mp4-64.11 MB
• ~Get Your Files Here !/011. Chapter 3. Computing the attention weights step by step.mp4-63.51 MB
• ~Get Your Files Here !/018. Chapter 4. Coding an LLM architecture.mp4-62.12 MB
• ~Get Your Files Here !/013. Chapter 3. Applying a causal attention mask.mp4-56.36 MB
• ~Get Your Files Here !/010. Chapter 3. A simple self-attention mechanism without trainable weights Part 2.mp4-54.97 MB
• ~Get Your Files Here !/036. Chapter 6. Creating data loaders.mp4-54.34 MB
• ~Get Your Files Here !/008. Chapter 2. Encoding word positions.mp4-49.18 MB
• ~Get Your Files Here !/042. Chapter 7. Preparing a dataset for supervised instruction fine-tuning.mp4-47.2 MB
• ~Get Your Files Here !/016. Chapter 3. Stacking multiple single-head attention layers.mp4-45.54 MB
• ~Get Your Files Here !/021. Chapter 4. Adding shortcut connections.mp4-44.29 MB
• ~Get Your Files Here !/047. Chapter 7. Extracting and saving responses.mp4-42.3 MB
• ~Get Your Files Here !/037. Chapter 6. Initializing a model with pretrained weights.mp4-42.27 MB
• ~Get Your Files Here !/030. Chapter 5. Temperature scaling.mp4-42.17 MB
• ~Get Your Files Here !/015. Chapter 3. Implementing a compact causal self-attention class.mp4-41.52 MB
• ~Get Your Files Here !/003. Chapter 2. Converting tokens into token IDs.mp4-39.96 MB
• ~Get Your Files Here !/041. Chapter 6. Using the LLM as a spam classifier.mp4-35.89 MB
• ~Get Your Files Here !/004. Chapter 2. Adding special context tokens.mp4-34.81 MB
• ~Get Your Files Here !/012. Chapter 3. Implementing a compact self-attention Python class.mp4-33.62 MB
• ~Get Your Files Here !/032. Chapter 5. Modifying the text generation function.mp4-33.45 MB
• ~Get Your Files Here !/007. Chapter 2. Creating token embeddings.mp4-32.81 MB
• ~Get Your Files Here !/044. Chapter 7. Creating data loaders for an instruction dataset.mp4-32.29 MB
• ~Get Your Files Here !/031. Chapter 5. Top-k sampling.mp4-26.26 MB
• ~Get Your Files Here !/045. Chapter 7. Loading a pretrained LLM.mp4-24.68 MB
• ~Get Your Files Here !/033. Chapter 5. Loading and saving model weights in PyTorch.mp4-22 MB
• ~Get Your Files Here !/029. Chapter 5. Decoding strategies to control randomness.mp4-20.07 MB
• ~Get Your Files Here !/014. Chapter 3. Masking additional attention weights with dropout.mp4-16.8 MB
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• ~Get Your Files Here !/Bonus Resources.txt-70 Bytes