Also their cuDF library will automatically know if you're running on GPU or CPU and speed up your processing. RAPIDS cuDF is now integrated directly into Google Colab. Checkout the Colab Notebook: https://
colab.research.google.com/github/rapidsa
i-community/showcase/blob/main/getting_started_tutorials/cudf_pandas_colab_demo.ipynb?ncid=ref-inor-594904
… Check out the Github Repo:
@sumanth_077
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RAPIDS cuDF Library Now Integrated into Google Colab
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NVIDIA accelerates Pandas 150x faster with minimal code changes
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Pandas is a powerful data analysis and manipulation library for Python!
— Sumanth (@Sumanth_077) 26 juin 2024
NVIDIA just made Pandas 150x faster with zero code changes🔥
All you have to add is just a couple of lines of code:
%load_ext cudf.pandas
import pandas as pd pic.twitter.com/5JKqte1tppPandas is a powerful data analysis and manipulation library for Python! NVIDIA just made Pandas 150x faster with zero code changes All you have to add is just a couple of lines of code: %load_ext cudf.pandas
import pandas as pd -
cuDF Pandas Accelerator: Accelerated Computing for Large Datasets
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Pandas operates in-memory, as it loads the entire dataset into the local memory of the machine it is running on. This limits its ability to handle large datasets. With cuDF’s pandas accelerator you can now bring accelerated computing to pandas workflows.
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Chat with Your Data: Summarizing PDF Files
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Step 4: Chat with your data Finally, once the data has been ingested into the app, chat with your data. Here we are asking it to summarize the pdf file.
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Daily Content on Python, Data Science, Machine Learning, and MLOps
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That's a wrap! If you are interested in any of these topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
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Upload PDF Research Paper Data to Clarifai App Vector Database
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Step 3: Upload the data, Here we are uploading the pdf file of a research paper. Once you upload the data, it will embed and index the data into your Clarifai app. Clarifai Apps acts as your vector database.
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Setting up RAG system with Clarifai and Claude 3.5 Sonnet
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Step 2: Next, import the RAG class and set up the RAG system by passing your Clarifai user ID and the Claude 3.5 Sonnet model URL from the Clarifai community. You can find it here: https://
clarifai.com/anthropic/comp
letion/models/claude-3_5-sonnet
… Once you sign up, you can find your user ID here: -
Install Clarifai Python SDK and Llama-index Setup Guide
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Step 1: Install the Clarifai Python SDK, Llama-index, and set your Clarifai Personal Access Token as an environment variable. Sign up for the platform, and you can access the PAT here: https://
clarifai.com/settings/secur
ity
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Build RAG System in 4 Lines Using Clarifai SDK
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You can build a RAG system with just 4 lines of code using @clarifai Python SDK. Below is the entire code. Let's look at it step by step:
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Build LLM RAG App Chat PDF Files Claude 3.5 Sonnet
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Build a LLM app with RAG to chat with PDF files using the latest Claude 3.5 Sonnet in just 4 lines of Python code (step-by-step guide):