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few-shot-prompting

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ksm26 / Prompt-Engineering-with-Llama-2

Star 7

The course provides guidance on best practices for prompting and building applications with the powerful open commercial license models of Llama 2.

natural-language-processing language-models responsible-ai ai-applications industry-standards prompt-engineering few-shot-prompting llama-2 code-llama safe-ai llama-guard meta-llama-2-chat chain-of-thought-prompting prompt-engineering-models open-commercial-license advanced-prompting-models responsible-ai-techniques llm-interaction
  • Updated Mar 27, 2024
  • Jupyter Notebook

saadtariq-ds / llms_with_google_cloud

Star 4

Leveraged the power of Google Cloud's Vertex AI platform to develop advanced Large Language Models (LLMs). Utilizing the Python API provided by Google Cloud, this endeavor represents a significant stride in the realm of natural language processing and LLMs.

python api natural-language-processing database chatbot gcp google-cloud text-generation code-generation text-embedding context-injection vertex-ai large-language-models prompt-engineering llms few-shot-prompting one-shot-prompting
  • Updated Nov 28, 2023
  • Jupyter Notebook

ElmiraGhorbani / dynamic_prompting

Star 3

Dynamic Few-Shot Prompting is a Python package that dynamically selects N samples that are contextually close to the user's task or query from a knowledge base (similar to RAG) to include in the prompt.

python nlp information-retrieval prompt llama gpt knowledge-base rag retreival few-shot-classifcation prompt-tuning llm prompt-engineering generative-ai few-shot-prompting retrieval-augmented-generation llama3 llama3-prompts
  • Updated Jul 12, 2024
  • Python

stefanshipinkoski / dynamic-few-shot-prompting-blog-post

Star 0

Dynamic Few-Shot Prompting for Customer Support AI Agents A practical implementation of dynamic few-shot prompting using LangChain and HuggingFace models. This repository provides an optimized approach to improving AI agent performance for customer support tasks by selecting relevant examples based on user queries, thus enhancing response accuracy

open-source blog-post few-shot-learning huggingface llm prompt-engineering generative-ai few-shot-prompting dynamic-prompting
  • Updated Nov 20, 2024
  • Python

at-akshat-2107 / LJMU-Thesis-Results-Akshat-Mehta-1129239

Star 0

This repository contains results from my MSc. thesis on "Test Case Generation from User Stories using Generative AI Techniques with LLM Models." Each folder includes generated test cases in PDF, detailed metrics scores of data in Excel sheets, and visual graphs, offering a comprehensive view of the experiments in images folder and their outcomes.

python3 zero-shot zero-shot-learning few-shot explainable-ai testcase-generator few-shot-learning chain-of-thought few-shot-prompting genai tree-of-thoughts chain-of-thought-reasoning testgpt chain-of-thought-prompting story2testgpt
  • Updated Sep 9, 2024
  • Jupyter Notebook

satyampurwar / large-language-models

Star 0

Unlocking the Power of Generative AI: In-Context Learning, Instruction Fine-Tuning and Reinforcement Learning Fine-Tuning.

memory-management bert conda-environment kl-divergence encoder-decoder-model proximal-policy-optimization encoder-model storage-management megacmd model-quantization large-language-models prompt-engineering generative-ai reinforcement-learning-from-human-feedback flan-t5 few-shot-prompting low-rank-adaptation reinforcement-learning-from-ai-feedback peft-fine-tuning-llm instruction-fine-tuning
  • Updated Oct 25, 2024
  • Jupyter Notebook

simonpierreboucher / llm_multiple_generation

Star 0

This repository contains Jupyter notebooks demonstrating various generation tasks with Large Language Models (LLMs). It provides examples for summarization, text generation, few-shot learning, and translation, utilizing different LLM APIs to showcase the capabilities of multiple providers.

translation openai summary mistral few-shot large-language-models llm anthropic few-shot-prompting
  • Updated Nov 14, 2024
  • Jupyter Notebook

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