Both models also benchmark impressively well against commercial models. replit-finetuned-v1-3b is by far the smallest model on the table and it outperformed Codex and LLaMA. PaLM-Coder is 200x larger and we’re closing in on their performance with much better latency.
CODE
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Code Model Demonstrates Surprising Non-Coding Reasoning Capabilities
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We also noticed a surprising capability in non-coding reasoning, despite the model being trained entirely on code. We benchmarked against models trained for reasoning tasks and replit-code-v1-3b performed incredibly well.
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Replit Code Models Outperform Larger Open Source Competitors
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Replit-code-v1-3b & replit-finetuned-v1-3b were trained entirely on code and were meant for single-line code completion. We didn’t expect either to perform so well on HumanEval, but they did. replit-finetuned-v1-3b outperformed all OSS code models, even those 5x its size.
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Replit Open-Sources Complete Code Model 2.7B
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At #ReplitDevDay, we announced we’ve trained and are open-sourcing our first Complete Code model. Introducing replit-code-v1-3b: – 2.7B params
– 20 languages
– 525B tokens
– 40% better than comparable models
– Trained in 10 days Take a look at the benchmarks yourself -
TF-IDF Fundamentals: Term Frequency and Inverse Document Frequency
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Le TF IDF n'a aucun rapport entre le machine learning et le SEO. Term frequency Inverse document frequency
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AutoTrain Advanced Now Supports LLM Finetuning
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AutoTrain Advanced supports LLM finetuning now! More details come tomorrow! Stay tuned or try without documentation/walkthrough if you dare 😉
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Replit Launches Major Platform Upgrades at ReplitDevDay
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Yesterday, we launched a flurry of the most significant upgrades to ever come to Replit. If you couldn't tune in to #ReplitDevDay, you're in luck. We just released the keynote. Watch til the end to see our most exciting announcement .
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YOLO Object Detection Tutorials with Python PyTorch Resources
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Dozens of #ComputerVision tutorials on different applications of YOLO models for #ObjectDetection and Classification using #Python and #PyTorch:
– tutorials:
https://
youtube.com/watch?v=fFCWrM
FH2UY&list=PLZCA39VpuaZZJ-aS7B7pZVrD9AtRx8-7u
…
– Github notebooks: https://
github.com/roboflow/noteb
ooks
… #DataScience #AI #DeepLearning #MachineLearning -
DevOps Collaboration Improves Software Quality Through Better Requirements
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DevOps enables the formation of a unique and collaborative team that allows a better requirements analysis and a consequent increase in the quality of the software. Microblog and social design by @antgrasso #DevOps #SoftwareDevelopment
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NeMo Guardrails: Trustworthy LLM Application Development Toolkit
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NeMo Guardrails, a toolkit for developing trustworthy LLM-based conversational applications. It works with all #LLMs and natively supports @langchain
, adding a layer of safety, security, and topical guardrails to existing applications. – @NVIDIAAI https://
nvda.ws/3NfoDrC