| 001. Chapter 1. Python Environment Setup.mp4 | 90.2 MB | ||
| 002. Chapter 2. Tokenizing text.mp4 | 99.1 MB | ||
| 003. Chapter 2. Converting tokens into token IDs.mp4 | 40 MB | ||
| 004. Chapter 2. Adding special context tokens.mp4 | 34.8 MB | ||
| 005. Chapter 2. Byte pair encoding.mp4 | 69.7 MB | ||
| 006. Chapter 2. Data sampling with a sliding window.mp4 | 91.9 MB | ||
| 007. Chapter 2. Creating token embeddings.mp4 | 32.8 MB | ||
| 008. Chapter 2. Encoding word positions.mp4 | 49.2 MB | ||
| 009. Chapter 3. A simple self-attention mechanism without trainable weights Part 1.mp4 | 173.9 MB | ||
| 010. Chapter 3. A simple self-attention mechanism without trainable weights Part 2.mp4 | 55 MB | ||
| 011. Chapter 3. Computing the attention weights step by step.mp4 | 63.5 MB | ||
| 012. Chapter 3. Implementing a compact self-attention Python class.mp4 | 33.6 MB | ||
| 013. Chapter 3. Applying a causal attention mask.mp4 | 56.4 MB | ||
| 014. Chapter 3. Masking additional attention weights with dropout.mp4 | 16.8 MB | ||
| 015. Chapter 3. Implementing a compact causal self-attention class.mp4 | 41.5 MB | ||
| 016. Chapter 3. Stacking multiple single-head attention layers.mp4 | 45.5 MB | ||
| 017. Chapter 3. Implementing multi-head attention with weight splits.mp4 | 127.1 MB | ||
| 018. Chapter 4. Coding an LLM architecture.mp4 | 62.1 MB | ||
| 019. Chapter 4. Normalizing activations with layer normalization.mp4 | 84 MB | ||
| 020. Chapter 4. Implementing a feed forward network with GELU activations.mp4 | 102.1 MB | ||
| 021. Chapter 4. Adding shortcut connections.mp4 | 44.3 MB | ||
| 022. Chapter 4. Connecting attention and linear layers in a transformer block.mp4 | 64.1 MB | ||
| 023. Chapter 4. Coding the GPT model.mp4 | 67 MB | ||
| 024. Chapter 4. Generating text.mp4 | 65.7 MB | ||
| 025. Chapter 5. Using GPT to generate text.mp4 | 71.6 MB | ||
| 026. Chapter 5. Calculating the text generation loss cross entropy and perplexity.mp4 | 97.6 MB | ||
| 027. Chapter 5. Calculating the training and validation set losses.mp4 | 94.7 MB | ||
| 028. Chapter 5. Training an LLM.mp4 | 138.8 MB | ||
| 029. Chapter 5. Decoding strategies to control randomness.mp4 | 20.1 MB | ||
| 030. Chapter 5. Temperature scaling.mp4 | 42.2 MB | ||
| 031. Chapter 5. Top-k sampling.mp4 | 26.3 MB | ||
| 032. Chapter 5. Modifying the text generation function.mp4 | 33.5 MB | ||
| 033. Chapter 5. Loading and saving model weights in PyTorch.mp4 | 22 MB | ||
| 034. Chapter 5. Loading pretrained weights from OpenAI.mp4 | 106.6 MB | ||
| 035. Chapter 6. Preparing the dataset.mp4 | 103.8 MB | ||
| 036. Chapter 6. Creating data loaders.mp4 | 54.3 MB | ||
| 037. Chapter 6. Initializing a model with pretrained weights.mp4 | 42.3 MB | ||
| 038. Chapter 6. Adding a classification head.mp4 | 73.7 MB | ||
| 039. Chapter 6. Calculating the classification loss and accuracy.mp4 | 64.5 MB | ||
| 040. Chapter 6. Fine-tuning the model on supervised data.mp4 | 162.7 MB | ||
| 041. Chapter 6. Using the LLM as a spam classifier.mp4 | 35.9 MB | ||
| 042. Chapter 7. Preparing a dataset for supervised instruction fine-tuning.mp4 | 47.2 MB | ||
| 043. Chapter 7. Organizing data into training batches.mp4 | 79.8 MB | ||
| 044. Chapter 7. Creating data loaders for an instruction dataset.mp4 | 32.3 MB | ||
| 045. Chapter 7. Loading a pretrained LLM.mp4 | 24.7 MB | ||
| 046. Chapter 7. Fine-tuning the LLM on instruction data.mp4 | 98.2 MB | ||
| 047. Chapter 7. Extracting and saving responses.mp4 | 42.3 MB | ||
| 048. Chapter 7. Evaluating the fine-tuned LLM.mp4 | 102.1 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 50 total files | |||
Code with the Author of Build an LLM (From Scratch)
https://WebToolTip.com
May 2025 | MP4 | Video: h264, 1920x1080| Audio: AAC, 44.1 KHz
Language: English | Size: 3.15 GB | Duration: 13h 35m
Master the inner workings of how large language models like GPT really work with hands-on coding sessions led by bestselling author Sebastian Raschka.
These companion videos to Build a Large Language Model from Scratch walk you through real-world implementation, with each session ending in a “test yourself” challenge to solidify your skills and deepen your understanding.
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| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.4 GB | freecoursewb | 1 month | 28 | 1 | |
| 858.6 MB | freecoursewb | 1 month | 0 | 0 | |
| 1.9 GB | freecoursewb | 2 months | 28 | 14 | |
| 1.9 GB | freecoursewb | 3 months | 13 | 0 | |
| 2.2 GB | freecoursewb | 3 months | 52 | 5 |
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