trulens
LIME
trulens | LIME | |
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14 | 2 | |
1,629 | 14 | |
6.9% | - | |
9.8 | 0.0 | |
about 8 hours ago | almost 3 years ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
trulens
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Why Vector Compression Matters
Retrieval using a single vector is called dense passage retrieval (DPR), because an entire passage (dozens to hundreds of tokens) is encoded as a single vector. ColBERT instead encodes a vector-per-token, where each vector is influenced by surrounding context. This leads to meaningfully better results; for example, here’s ColBERT running on Astra DB compared to DPR using openai-v3-small vectors, compared with TruLens for the Braintrust Coda Help Desk data set. ColBERT easily beats DPR at correctness, context relevance, and groundedness.
- FLaNK AI Weekly 18 March 2024
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First 15 Open Source Advent projects
12. TruLens by TruEra | Github | tutorial
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trulens VS agenta - a user suggested alternative
2 projects | 22 Nov 2023
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How are generative AI companies monitoring their systems in production?
3) Hallucination is probably the biggest problem we solve for. To do evals for hallucination, we typically see our users use a combination of groundedness (does the context support the LLM response) and context relevance (is the retrieved context relevant to the query). There's also a bunch more for the evaluations you mentioned (moderation models, sentiment, usefulness, etc.) and it's pretty easy to add custom evals.
Also - my hot take is that gpt-3.5 is good enough for evals (sometimes better) than gpt-4 if you give the LLM enough instructions on how to do the eval.
website: https://www.trulens.org/
- FLaNK Stack Weekly 28 August 2023
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[P] TruLens-Eval is an open source project for eval & tracking LLM experiments.
The team at TruEra recently released an open source project for evaluation & tracking of LLM applications called TruLens-Eval. We’ve specifically targeted retrieval-augmented QA as a core use case and so far we’ve seen it used for comparing different models and parameters, prompts, vector-db configurations and query planning strategies. I’d love to get your feedback on it.
- [D] Hardest thing about building with LLMs?
- Stop Evaluating LLMs on Vibes
- OSS library for attribution and interpretation methods for deep nets
LIME
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[Explainable AI] Interpret complex neural network's decisions with simple linear regressions
I am very glad you liked it and thank you for your hint. In terms of citation, I never claimed the algorithm to be mine. But the implementation is 100% my work and the notebooks themselves are also only for educational purpose (university's course). On GitHub where the project's is hosted, I referenced the original author's work at the first place to ensure scientific integrity (https://github.com/longmakesstuff/LIME).
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Explainable AI: Interpreting black box models with simple linear regression
Basically, we desire to interpret how a black box model made its decision for a single sample. The code can be found at: https://github.com/longmakesstuff/LIME
What are some alternatives?
langfuse - 🪢 Open source LLM engineering platform: Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
DALEX - moDel Agnostic Language for Exploration and eXplanation
probability - Probabilistic reasoning and statistical analysis in TensorFlow
embedchain - Personalizing LLM Responses
machine_learning_basics - Plain python implementations of basic machine learning algorithms
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
llama-gpt - A self-hosted, offline, ChatGPT-like chatbot. Powered by Llama 2. 100% private, with no data leaving your device. New: Code Llama support!
LANDrop - Drop any files to any devices on your LAN.
fish-shell - The user-friendly command line shell.