alpaca_eval
llm-search
| alpaca_eval | llm-search | |
|---|---|---|
| 4 | 2 | |
| 1,134 | 381 | |
| 10.0% | - | |
| 9.6 | 8.5 | |
| 7 days ago | about 1 month ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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alpaca_eval
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UltraLM-13B reaches top of AlpacaEval leaderboard
Alpaca Eval is open source and was developed by the same team who trained the alpaca model afaik. It is not like what you said in the other comment
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[P] AlpacaEval : An Automatic Evaluator for Instruction-following Language Models
I have been going deep in this space for my can-ai-code project and was looking at the config that WizardLM was run with: https://github.com/tatsu-lab/alpaca_eval/blob/main/src/alpaca_eval/models_configs/wizardlm-13b/configs.yaml
an automatic evaluator that is easy to use, fast, cheap and validated against 20K human annotations. It actually has a higher agreement with majority vote of humans than a single human annotator! Of course, our method still has limitations which we discuss here!
llm-search
- Querying local documents, powered by LLM
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I can't find a code example of using a prompt in langchain with a GGML quantized llama-based model!
Here is an example how to create a custom class for langchain - https://github.com/snexus/llm-search/blob/main/src/llmsearch/models/llama.py It is calling llama-cpp-python behind the scenes
What are some alternatives?
Local-LLM-Comparison-Colab-UI - Compare the performance of different LLM that can be deployed locally on consumer hardware. Run yourself with Colab WebUI.
DeepLearningExamples - State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
ReAct - [ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models
FinGPT - FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
EasyEdit - An Easy-to-use Knowledge Editing Framework for LLMs.
alpaca_farm - A simulation framework for RLHF and alternatives. Develop your RLHF method without collecting human data.
medmcqa - A large-scale (194k), Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.
anything-llm - The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities.
language-planner - Official Code for "Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents"
hyde - HyDE: Precise Zero-Shot Dense Retrieval without Relevance Labels