Pre-Trained Language Models AND NLP@Stanford
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17 Documents
bclavie/RAGatouille
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2024-01-26 About
Zain Hasan sur X : "why do large language models pay more attention to and reason better over the beginning and end of what you tell them in prompts?"
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2023-11-19 About
LangChain Retrieval Webinar - YouTube
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2023-05-27 About
How to use Alpaca-LoRA to fine-tune a model like ChatGPT
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2023-05-26 About
Daniel Vila Suero sur Twitter : "Data quality is key for LLMs, but we're building Open Source LLMs with data of "unknown" quality... Introducing Alpaca GarbageCollector..."
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2023-04-05 About
Alpaca Finetuning of Llama on a 24G Consumer GPU
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2023-03-27 About
tloen/alpaca-lora: Instruct-tune LLaMA on consumer hardware
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2023-03-22 About
LLM Zoo at Home: LLaMA & Alpaca | bergis universe of software, hardware and ideas
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2023-03-20 About
stanfordnlp/dspy: 𝗗𝗦𝗣: Demonstrate-Search-Predict. A framework for composing retrieval and language models for knowledge-intensive NLP.
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2023-02-18 About
Prompting, Instruction Finetuning, and RLHF (CS224N)
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2023-02-16 About
[2203.14465] STaR: Bootstrapping Reasoning With Reasoning
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2023-02-07 About
Meet CoAuthor, an Experiment in Human-AI Collaborative Writing
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2022-11-13 About
[2208.01066] What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
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2022-09-17 About
[2006.05987] Revisiting Few-sample BERT Fine-tuning
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2022-03-21 About
Document Matching for Job Descriptions | Semantic Scholar (2021)
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2022-03-09 About
BERT, ELMo, & GPT-2: How Contextual are Contextualized Word Representations? | SAIL Blog
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2020-03-28 About
Lecture 14 – Contextual Vectors | Stanford CS224U: Natural Language Understanding | Spring 2019
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2020-01-05 About