Python library that adds Generative AI capabilities to Pandas Introducing PandasAI, now you can analyze complex data frames and plot visualizations just by using natural language:
OPEN SOURCE
-
FineWeb Extended Report and Blog Post Coming Soon
By
–
We're finishing a pretty awesome extended blogpost/report on FineWeb in which you'll find all the info – stay tuned!
-
Keras Compiles to JAX, TensorFlow, PyTorch with JAX Recommended
By
–
Keras code compiles to JAX, TensorFlow, or PyTorch code, so anything you can do with one of these frameworks you can do with Keras. I recommend using JAX as your backend, as it is suitable for very-large scale computation and can be easily parallelized across many devices.
-
Keras ops API: NumPy syntax across JAX PyTorch TensorFlow
By
–
A neat feature of Keras is that its `keras.ops` API follows the NumPy API syntax exactly. And since it runs on JAX, PyTorch, TensorFlow, and NumPy itself, you can use Keras to write GPU-accelerated NumPy code that runs with any framework.
-
Reproduce GPT-2 124M in llm.c for $20 in 90 Minutes
By
–
# Reproduce GPT-2 (124M) in llm.c in 90 minutes for $20 The GPT-2 (124M) is the smallest model in the GPT-2 series released by OpenAI in 2019, and is actually quite accessible today, even for the GPU poor. For example, with llm.c you can now reproduce this model on one 8X
-
Running Multiple Open Source LLMs Locally with Ollama
By
–
Check out the code and complete hands on tutorial in the below blog https://
blog.futuresmart.ai/running-multip
le-open-source-llms-locally-with-ollama
…
#FuturesmartAI #AI #LLMs #Opensource -
Ollama: Running Open-Source LLMs Locally on Your PC
By
–
Ollama is a tool designed for this purpose, enabling you to run open-source LLMs like Mistral, Llama2, and Llama3 on your PC. Running LLMs can help to maintain privacy, reduced latency, and customisation as per your requirements.
-
Running Large Language Models Locally: Privacy and Performance Benefits
By
–
Large language models (LLMs) are being used in various applications, from chatbots to content generation. While cloud-based LLMs are popular, running them locally has advantages like enhanced privacy, reduced latency, and more customisation.
-
Running Multiple Open Source LLMs Locally with Ollama
By
–
Running Multiple Open Source LLMs Locally with Ollama Check out this awesome blog on how to run LLMs on your local machine and build applications with ease
-
LeCun vs Musk: Open Research Scientists Drive Progress
By
–
I would pick @ylecun over @elonmusk every single day of the week. Despite getting much less $$, recognition & visibility than entrepreneurs, the scientists who publish their groundbreaking research openly are the cornerstone of technological progress & massively contribute to