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Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
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| .env |
121B |
| .gitattributes |
42B |
| .gitignore |
285B |
| 001. Module Introduction.mp4 |
21.98MB |
| 001. Module Introduction.mp4 |
19.68MB |
| 001. Module Introduction.mp4 |
27.49MB |
| 001. Quick Guide to ChatGPT, Embeddings, and Other Large Language Models (LLMs) Introduction.mp4 |
22.54MB |
| 001. Quick Guide to ChatGPT, Embeddings, and Other Large Language Models (LLMs) Summary.mp4 |
27.04MB |
| 001. Topics.mp4 |
5.98MB |
| 001. Topics.mp4 |
4.30MB |
| 001. Topics.mp4 |
5.29MB |
| 001. Topics.mp4 |
4.63MB |
| 001. Topics.mp4 |
5.17MB |
| 001. Topics.mp4 |
3.30MB |
| 001. Topics.mp4 |
4.96MB |
| 001. Topics.mp4 |
5.56MB |
| 001. Topics.mp4 |
5.68MB |
| 001. Topics.mp4 |
5.76MB |
| 001. Topics.mp4 |
4.03MB |
| 001. Topics.mp4 |
4.19MB |
| 002. 1.1 What Are Large Language Models.mp4 |
120.87MB |
| 002. 10.1 BERT for Multi-label Classification Part 1.mp4 |
55.19MB |
| 002. 11.1 Cost Projecting and Deploying LLMs to Production.mp4 |
39.86MB |
| 002. 12.1 Evaluating Generative Tasks Part 1.mp4 |
71.52MB |
| 002. 2.1 Introduction to Semantic Search.mp4 |
64.18MB |
| 002. 3.1 Introduction to Prompt Engineering.mp4 |
121.85MB |
| 002. 4.1 Introduction to Retrival Augmented Generation (RAG).mp4 |
54.13MB |
| 002. 5.1 Transfer Learning A Primer.mp4 |
26.17MB |
| 002. 6.1 InputOutput Validation.mp4 |
46.03MB |
| 002. 7.1 Case Study Building an Anime Recommendation System.mp4 |
53.87MB |
| 002. 8.1 Introduction to AI Alignment.mp4 |
72.04MB |
| 002. 9.1 The Vision Transformer.mp4 |
13.29MB |
| 003. 1.2 Popular Modern LLMs.mp4 |
97.86MB |
| 003. 10.2 BERT for Multi-label Classification Part 2.mp4 |
125.25MB |
| 003. 11.2 Knowledge Distillation.mp4 |
107.93MB |
| 003. 12.2 Evaluating Generative Tasks Part 2.mp4 |
107.56MB |
| 003. 2.2 Building a Semantic Search System.mp4 |
148.61MB |
| 003. 3.2 Working with Prompts Across Models.mp4 |
22.42MB |
| 003. 4.2 Building a RAG bot.mp4 |
113.33MB |
| 003. 5.2 The OpenAI Fine-Tuning API.mp4 |
29.78MB |
| 003. 6.2 Batch Prompting + Prompt Chaining.mp4 |
40.08MB |
| 003. 7.2 Using OpenAI s Embedded Models.mp4 |
120.55MB |
| 003. 8.2 Evaluating Alignment Plus Ethics.mp4 |
91.52MB |
| 003. 9.2 Using Cross Attention to Mix Data Modalities.mp4 |
17.72MB |
| 004. 1.3 Applications of LLMs.mp4 |
16.26MB |
| 004. 10.3 Writing LaTeX with GPT-2.mp4 |
89.99MB |
| 004. 12.3 Evaluating Understanding Tasks.mp4 |
100.80MB |
| 004. 2.3 Optimizing Semantic Search with Cross-Encoders and Fine-Tuning.mp4 |
160.95MB |
| 004. 3.3 Building a Retrieval-Augmented Generation BOT with ChatGPT and GPT-4.mp4 |
170.80MB |
| 004. 4.3 Using Open Source Models with RAG.mp4 |
103.61MB |
| 004. 5.3 Case Study Predicting with Android App Reviews Part 1.mp4 |
37.35MB |
| 004. 6.3 Chain-of-Thought Prompting.mp4 |
60.08MB |
| 004. 7.3 Fine-tuning an Embedding Model to Capture User Behavior.mp4 |
152.09MB |
| 004. 9.3 Case Study Visual QA Setting Up Our Model.mp4 |
112.92MB |
| 005. 10.4 Case Study Sinan s Attempt at Wise Yet Engaging Responses Sawye.mp4 |
100.07MB |
| 005. 12.4 Probing LLMs for world model.mp4 |
48.76MB |
| 005. 4.4 Expanding into AI Agents.mp4 |
116.64MB |
| 005. 5.4 Case Study Predicting with Android App Reviews Part 2.mp4 |
224.34MB |
| 005. 6.4 Preventing Prompt Injection Attacks.mp4 |
21.51MB |
| 005. 9.4 Case Study Visual QA Setting Up Our Parameters and Data.mp4 |
105.41MB |
| 006. 10.5 Instruction Alignment of LLMs Supervised Fine-Tuning.mp4 |
172.22MB |
| 006. 6.5 Assessing an LLM s Encoded Knowledge Level.mp4 |
27.96MB |
| 006. 9.5 Introduction to Reinforcement Learning from Feedback.mp4 |
58.54MB |
| 007. 10.6 Instruction Alignment of LLMs Reward Modeling.mp4 |
143.83MB |
| 007. 9.6 Aligning FLAN-T5 with Reinforcement Learning from Feedback.mp4 |
130.07MB |
| 008. 10.7 Instruction Alignment of LLMs RLHF.mp4 |
164.15MB |
| 009. 10.8 Instruction Alignment of LLMs Using Our Instruction-Aligned LLM.mp4 |
118.99MB |
| 02_semantic_search.ipynb |
438.03KB |
| 03_prompt_engineering.ipynb |
35.78KB |
| 04_agent.ipynb |
1.37MB |
| 04_rag_retrieval.ipynb |
25.79KB |
| 05_bert_app_review.ipynb |
101.15KB |
| 05_openai_app_review_fine_tuning.ipynb |
2.03MB |
| 06_adv_prompt_engineering.ipynb |
1.07MB |
| 06_adv_prompt_engineering - DEEPSEEK.ipynb |
510.06KB |
| 07_recommendation_engine.ipynb |
1.07MB |
| 09_constructing_a_vqa_system.ipynb |
326.31KB |
| 09_flan_t5_rl.ipynb |
430.56KB |
| 09_using_our_vqa.ipynb |
3.50MB |
| 10_anime_category_classification_model_freezing.ipynb |
1.57MB |
| 10_latex_gpt2.ipynb |
65.20KB |
| 10_optimizing_fine_tuning.ipynb |
313.89KB |
| 10_SAWYER_LLAMA_SFT.ipynb |
616.56KB |
| 10_SAWYER_Reward_Model.ipynb |
232.21KB |
| 10_SAWYER_RLF.ipynb |
756.44KB |
| 10_SAWYER_USE_SAWYER.ipynb |
1.43MB |
| 11_distillation_example_1.ipynb |
310.09KB |
| 11_distillation_example_2.ipynb |
475.09KB |
| 11_llama_quantization.ipynb |
438.31KB |
| 12_cluster.ipynb |
436.59KB |
| 12_llm_calibration.ipynb |
661.45KB |
| 12_llm_gen_eval.ipynb |
999.08KB |
| api.py |
5.35KB |
| chip2.csv |
133B |
| chunking_utils.py |
1.99KB |
| comparison_data_v2.json |
77.70MB |
| conversation_utils.py |
5.57KB |
| Dockerfile |
214B |
| english_to_latex.csv |
129B |
| gpt3_paper.png |
30.42KB |
| latex-guide-cos423.txt |
16.30KB |
| pds2.pdf |
15.96MB |
| pre_merged_anime.csv |
132B |
| pre_merged_anime.csv |
132B |
| qsllm.jpeg |
63.71KB |
| qsllm2e.jpg |
119.80KB |
| rating_complete.csv |
134B |
| README.md |
7.29KB |
| README.md |
3.33KB |
| requirements.txt |
89B |
| requirements.txt |
151B |
| retrieval_utils.py |
947B |
| watching_status.csv |
127B |