Run UI & Trainings locally NOW! No-code, state of the art model training. “`
$ pip install autotrain-advanced
$ export HF_TOKEN=your_hf_write_token
$ autotrain app
“`
CODE
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Run UI and Model Training Locally with AutoTrain Advanced
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Fine-tuning Language Models with Predefined Prompt Structures
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Also, a question: When you fine-tune a model that had a predefined prompt structure, like, let's say, Mistral for instance with its [INST] Instruction [/INST] do you use that in the fine-tuning process too when you're feeding the new strings?
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Coding with Images Gets Major Upgrade
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Coding with images just got a bit of an upgrade… pic.twitter.com/We0y5pQy8e
— Cursor (@cursor_ai) 6 février 2024Coding with images just got a bit of an upgrade…
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TensorFlow GNN 1.0 Released for Production-Scale Graph Neural Networks
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Graph neural networks (GNNs) have emerged as a powerful technique to leverage the uniquely heterogenous data from graphs. So, we are excited to announce the release of TensorFlow GNN 1.0 (TF-GNN), a production-tested library for building GNNs at scale → https://t.co/sJ6LDVyHuR pic.twitter.com/5ZM8gEDE6q
— Google AI (@GoogleAI) 6 février 2024Graph neural networks (GNNs) have emerged as a powerful technique to leverage the uniquely heterogenous data from graphs. So, we are excited to announce the release of TensorFlow GNN 1.0 (TF-GNN), a production-tested library for building GNNs at scale → https://
goo.gle/3w8ogZC -
Guide complet : fine-tuner vos LLMs efficacement
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Ready to #finetune but don't know where to start? We got you covered! Answers to your 4 biggest questions: When to fine-tune your #LLMs How to prepare your data What does it take to manage #infra How to reliably + #efficiently fine-tune
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TT-Metalium Open Source AI Stack Released
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Check out our #opensource stack TT-Metalium on @hackernews https://
news.ycombinator.com/item?id=392620
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WebVoyager: AI Agent for Autonomous Web Navigation
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2/ To jump straight to the code, check out the links below. Python Code:
https://
github.com/langchain-ai/l
anggraph/blob/main/examples/web-navigation/web_voyager.ipynb
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WebVoyager Paper:
https://
arxiv.org/abs/2401.13919
Set-of-Mark Paper:
https://
arxiv.org/abs/2310.11441 -
Developing AI Agents Easier with LangSmith
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3/ Developing agents like WebVoyager is easier with easier with LangSmith. Sign up at
https://
smith.langchain.com to get started. -
RAG From Scratch: New Video Series on LLM Integration
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RAG From Scratch: series focused on understanding the RAG landscape RAG is central for LLM application development, connecting LLMs to external data sources. But, the pace of innovation and new approaches makes it challenging to keep up. We're launching a new video