filmov
tv
Fine-tuning Llama 2 for Tone or Style
Показать описание
Fine-tune Llama 2 (or any huggingface model!) for tone or style using a custom dataset - here, Shakespeare!
*Free Resources*
1. Create Embeddings with OpenAI, marco, or Llama 2.
2. Run inference with injected embeddings
- Run fine-tuning using a Q&A dataset.
*Fine-tuning Repository Access*
1. Supervised Fine-tuning Notebook
2. Q&A Dataset Preparation Scripts
3. Embedding Notebook (Scripts to create and use Embeddings)
4. Notebook to fine-tune for Tone or Style
5. Forum Support
Chapters:
0:00 How to fine tune on a custom dataset
0:15 What dataset should I use for fine-tuning?
0:50 Fine-tuning in Google Colab
2:45 Loading Llama 2 with bitsandbytes
3:15 Fine-tuning with LoRA
3:50 Target modules for fine-tuning
4:15 Loading data for fine-tuning
5:30 Training Llama 2 with a validation set
6:30 Setting training parameters for fine-tuning
7:50 Choosing batch size for training
8:15 Setting gradient accumulation for training
9:25 Using an eval dataset for training
9:50 Setting warm-up parameters for training
10:50 Using AdamW for optimisation
13:20 Fix for when commands don't work in Colab
15:00 Evaluating training loss
16:20 Running inference after training
*Free Resources*
1. Create Embeddings with OpenAI, marco, or Llama 2.
2. Run inference with injected embeddings
- Run fine-tuning using a Q&A dataset.
*Fine-tuning Repository Access*
1. Supervised Fine-tuning Notebook
2. Q&A Dataset Preparation Scripts
3. Embedding Notebook (Scripts to create and use Embeddings)
4. Notebook to fine-tune for Tone or Style
5. Forum Support
Chapters:
0:00 How to fine tune on a custom dataset
0:15 What dataset should I use for fine-tuning?
0:50 Fine-tuning in Google Colab
2:45 Loading Llama 2 with bitsandbytes
3:15 Fine-tuning with LoRA
3:50 Target modules for fine-tuning
4:15 Loading data for fine-tuning
5:30 Training Llama 2 with a validation set
6:30 Setting training parameters for fine-tuning
7:50 Choosing batch size for training
8:15 Setting gradient accumulation for training
9:25 Using an eval dataset for training
9:50 Setting warm-up parameters for training
10:50 Using AdamW for optimisation
13:20 Fix for when commands don't work in Colab
15:00 Evaluating training loss
16:20 Running inference after training
0:09:44
Fine Tune LLaMA 2 In FIVE MINUTES! - 'Perform 10x Better For My Use Case'
0:17:30
Fine-tuning Llama 2 for Tone or Style
0:10:54
How to Fine-tune Llama 2 Model with Custom Dataset
0:28:57
Lessons From Fine-Tuning Llama-2
0:10:41
How to Fine-Tune and Train LLMs With Your Own Data EASILY and FAST- GPT-LLM-Trainer
0:09:11
Create Custom AI Characters Easily 🎭 How To Fine-Tune LLMs For AI Role Play
1:05:27
Fine-tuning Language Models for Structured Responses with QLoRa
0:21:54
Llama 3.2 Fine Tuning for Dummies (with 16k, 32k,... Context)
0:10:24
Use TorchTune to Fine Tune Llama 3 Locally
0:15:46
Tutorial 2- Fine Tuning Pretrained Model On Custom Dataset Using 🤗 Transformer
0:08:33
What is Prompt Tuning?
0:48:58
Embeddings vs Fine Tuning - Part 2, Supervised Fine-tuning
0:06:29
Fine-Tune ChatGPT For Your Exact Use Case
0:25:34
'I want Llama3.1 to perform 10x with my private knowledge' - Self learning Local Llama3.1 ...
0:09:40
Fine Tuning ChatGPT is a Waste of Your Time
0:00:50
How to Fine-Tune ChatGPT 👍
0:16:27
Control Tone & Writing Style Of Your LLM Output
0:24:48
Fine-Tuning The Best Models & More AI Use Cases
0:05:00
ADVANCED FINE TUNING SCRIPTS
0:59:35
Building with Instruction-Tuned LLMs: A Step-by-Step Guide
0:46:11
Fine-tuning in Your Voice Webinar
0:58:11
Training & Fine-Tuning LLMs: Data
0:09:40
How to Fine-tune OpenAI's GPT-3.5 Turbo for a Custom Tone
0:07:26
Fine Tune GPT In FIVE MINUTES with RLHF! - 'Perform 10x Better For My Use Case' - FREE COL...
Комментарии