4.7 (242) · $ 14.99 · In stock
Step by step hands-on tutorial to fine-tune a falcon-7 model using a open assistant dataset to make a general purpose chatbot. A complete guide to fine tuning llms
LLM models undergo training on extensive text data sets, equipping them to grasp human language in depth and context.
In the past, most models underwent training using the supervised method, where input features and corresponding labels were fed. In contrast, LLMs take a different route by undergoing unsupervised learning.
In this process, they consume vast volumes of text data devoid of any labels or explicit instructions. Consequently, LLMs efficiently learn the significance and interconnect
Fine-Tuning the Falcon LLM 7-Billion Parameter Model on Intel
How to fine tune Falcon LLM on custom dataset, Falcon 7B fine tune tutorial
Deploy Falcon-7b-instruct in under 15 minutes using UbiOps - UbiOps - AI model serving, orchestration & training
fine-tuning of large language models - Labellerr
Fine-Tuning Tutorial: Falcon-7b LLM To A General Purpose Chatbot
Alpaca and LLaMA: Inference and Evaluation MLExpert - Crush Your Machine Learning interview
Train Your Own GPT
Hugging Face Falcon-7B Large Language Model - Cloudbooklet AI
How-To Instruct Fine-Tuning Falcon-7B [Google Colab Included]
Finetuning an LLM: RLHF and alternatives (Part I), by Jose J. Martinez, MantisNLP
Finetuning Falcon LLMs More Efficiently With LoRA and Adapters
Private Chatbot with Local LLM (Falcon 7B) and LangChain
2306.14895] Large Multimodal Models: Notes on CVPR 2023 Tutorial
Finetuning an LLM: RLHF and alternatives (Part I)
Deploying Falcon-7B Into Production, by Het Trivedi