LinkedIn - Fine-Tuning for LLMs from Beginner to Advanced

[0dayddl]

526.96 MB | 00:14:08 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English


Files Included :

01 - Beginning to fine-tune your LLMs (3.9 MB)
02 - Getting the most out of this course (5.89 MB)
03 - Version check (3.45 MB)
01 - LLMs Revolutionizing AI (9.59 MB)
02 - The architecture of LLMs (7.01 MB)
03 - Applications of LLMs (9.16 MB)
04 - Ethical considerations in LLMs (6.92 MB)
05 - Comparing LLMs (10.91 MB)
06 - FLAN-T5 in focus (9.35 MB)
01 - Basics of prompt engineering (7.2 MB)
02 - Crafting effective prompts (9.92 MB)
03 - Prompt engineering with FLAN-T5 (11.51 MB)
04 - Demo Prompt engineering with FLAN-T5 (26.44 MB)
05 - Demo Using ICL and Patterns while prompting (18.53 MB)
06 - Case studies in prompt engineering (10.83 MB)
07 - Solution Designing a translation prompt (16.62 MB)
01 - Transfer learning in LLMs (11.55 MB)
02 - Choosing models for transfer learning (12.97 MB)
03 - Demo Transfer learning with FLAN-T5 (33.51 MB)
04 - Evaluating transfer learning outcomes (10.71 MB)
05 - Demo Evaluating translations (17.93 MB)
06 - Solution Enhancing translation with transfer learning (15.48 MB)
01 - Introduction to PEFT (14.61 MB)
02 - LoRA adapters (13.91 MB)
03 - LoRA in depth Technical analysis (12.22 MB)
04 - Demo LoRA fine-tuning on FLAN-T5 (43.7 MB)
05 - Implementing LoRA in LLMs (9.58 MB)
06 - Demo Challenges in LoRA (23.21 MB)
07 - Solution Fine-tuning FLAN-T5 for translation (21.58 MB)
01 - Solution Fine-tuning the sentiment analysis model (20.66 MB)
02 - Solution Fine-tuning the Q&A model (28.13 MB)
03 - Solution Fine-tuning the summarization model (19.08 MB)
04 - Demo Integrating everything into our solution (30.67 MB)
01 - Course recap and key takeaways (4.84 MB)
02 - Advanced topics and future trends in LLMs (4.17 MB)
03 - Leveraging LLMs for future projects (3.66 MB)
04 - Continuous learning in the field of LLMs (5.64 MB)

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