robertvacareanu / llm4regressionLinks
Examining how large language models (LLMs) perform across various synthetic regression tasks when given (input, output) examples in their context, without any parameter update
☆143Updated 8 months ago
Alternatives and similar repositories for llm4regression
Users that are interested in llm4regression are comparing it to the libraries listed below
Sorting:
- Lean implementation of various multi-agent LLM methods, including Iteration of Thought (IoT)☆113Updated 3 months ago
- One click away from a locally downloaded, fine-tuned model, hosted on hugging face, with inference built in. In two hours.☆22Updated 2 months ago
- ☆87Updated last year
- Set of scripts to finetune LLMs☆37Updated last year
- Swarming algorithms like PSO, Ant Colony, Sakana, and more in PyTorch 😊☆121Updated last week
- ☆49Updated 7 months ago
- ☆121Updated 2 months ago
- Codebase accompanying the Summary of a Haystack paper.☆78Updated 8 months ago
- Evaluation of neuro-symbolic engines☆35Updated 10 months ago
- ☆120Updated 10 months ago
- ☆130Updated 9 months ago
- Official implementation of MetaTree: Learning a Decision Tree Algorithm with Transformers☆110Updated 8 months ago
- Steer LLM outputs towards a certain topic/subject and enhance response capabilities using activation engineering by adding steering vecto…☆239Updated 3 months ago
- Training an LLM to use a calculator with multi-turn reinforcement learning, achieving a **62% absolute increase in evaluation accuracy**.☆38Updated last month
- Train your own SOTA deductive reasoning model☆93Updated 3 months ago
- Functional Benchmarks and the Reasoning Gap☆86Updated 8 months ago
- ☆118Updated 9 months ago
- Code for☆27Updated 5 months ago
- Simple replication of [ColBERT-v1](https://arxiv.org/abs/2004.12832).☆80Updated last year
- ☆38Updated 10 months ago
- Function Calling Benchmark & Testing☆87Updated 10 months ago
- ☆43Updated 7 months ago
- ☆68Updated 9 months ago
- QAlign is a new test-time alignment approach that improves language model performance by using Markov chain Monte Carlo methods.☆24Updated last month
- ☆83Updated 5 months ago
- ☆218Updated this week
- gzip Predicts Data-dependent Scaling Laws☆35Updated last year
- ☆77Updated last year
- Source code for the collaborative reasoner research project at Meta FAIR.☆87Updated last month
- A DSPy-based implementation of the tree of thoughts method (Yao et al., 2023) for generating persuasive arguments☆81Updated 8 months ago