GitHub - kaistAI/CoT-Collection: [Under Review] The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
š„¤ Cola [NeurIPS 2023]
Large Language Models are Visual Reasoning Coordinators
Liangyu Chen*,ā ,ā„ Bo Li*,ā„ Sheng Shenā£ Jingkang Yangā„
Chunyuan Liā Kurt Keutzerā£ Trevor Darrellā£ Ziwei Liuā,ā„
ā„S-Lab, Nanyang Technological University
ā£University of California, Berkeley ā Microsoft Research, Redmond
*Equal Contribution ā Project Lead āCorresponding Author... See more
Large Language Models are Visual Reasoning Coordinators
Liangyu Chen*,ā ,ā„ Bo Li*,ā„ Sheng Shenā£ Jingkang Yangā„
Chunyuan Liā Kurt Keutzerā£ Trevor Darrellā£ Ziwei Liuā,ā„
ā„S-Lab, Nanyang Technological University
ā£University of California, Berkeley ā Microsoft Research, Redmond
*Equal Contribution ā Project Lead āCorresponding Author... See more
cliangyu ā¢ GitHub - cliangyu/Cola: [NeurIPS2023] Official implementation of the paper "Large Language Models are Visual Reasoning Coordinators"
Nicolay Gerold added
GitHub - arthur-ai/bench: A tool for evaluating LLMs
GitHub - arthur-ai/bench: A tool for evaluating LLMs
BA Builder added
Phi-1.5
Phi-1.5 is a "small" 1.3 billion parameter LLM with an impressive performance for its size.
Annotated figures from the Textbooks Is All You Need II paper
How does this small model accomplish such a good performance? The secret ingredient seems to be the high-quality data.
The pretraining is based on the Textbooks Is All You Need approach that... See more
Phi-1.5 is a "small" 1.3 billion parameter LLM with an impressive performance for its size.
Annotated figures from the Textbooks Is All You Need II paper
How does this small model accomplish such a good performance? The secret ingredient seems to be the high-quality data.
The pretraining is based on the Textbooks Is All You Need approach that... See more
Sebastian Raschka ā¢ Ahead of AI #12: LLM Businesses and Busyness
Nicolay Gerold added
The authors hypothesize that the model gains instruction following capabilities without being instruction finetuning, which is an interesting observation.
The model may have unintentionally been trained using benchmark datasets (mirrors test cases, but fails when format changes).
Fine-Tuning for LLM Research by AI Hero
This repo contains the code that will be run inside the container. Alternatively, this code can also be run natively. The container is built and pushed to the repo using Github actions (see below). You can launch the fine tuning job using the examples in the https://github.com/ai-hero/llm-research-examples pr... See more
This repo contains the code that will be run inside the container. Alternatively, this code can also be run natively. The container is built and pushed to the repo using Github actions (see below). You can launch the fine tuning job using the examples in the https://github.com/ai-hero/llm-research-examples pr... See more
GitHub - ai-hero/llm-research-fine-tuning
Nicolay Gerold added
a couple of the top of my head:
- LLM in the loop with preference optimization
- synthetic data generation
- cross modality "distillation" / dictionary remapping
- constrained decoding
r/MachineLearning - Reddit
Nicolay Gerold added
Additional LLM paradigms beyond RAG
Many methods for creating these models don't (and to be honest can't) attach the name, website and other details of every image and piece of text used to a create a new image in the metadata to every step of the process.
Olu ā¢ Is using Lensa art theft? | The ethics of AI generated art
Isabelle Levent added
SteerLM leverages a supervised fine-tuning method that empowers you to control responses during inference. It overcomes the limitations of prior alignment techniques, and consists of four key steps:
- Train an attribute prediction model on human-annotated datasets to evaluate response quality on any number of attributes like helpfulness, humor, and cr
Yi Dong, Zhilin Wang ā¢ NVIDIA Technical Blog | News and tutorials for developers, data ...
Nicolay Gerold added
AgentTuning: Enabling Generalized Agent Abilities For LLMs
š¤ Model (AgentLM-70B) ā¢ š¤ Dataset (AgentInstruct) ā¢ š Paper ā¢ š Project Page
äøęē(Chinese)
AgentTuning represents the very first attempt to instruction-tune LLMs using interaction trajectories across multiple agent tasks. Evaluation results indicate that AgentTuning enables the agent capa... See more
š¤ Model (AgentLM-70B) ā¢ š¤ Dataset (AgentInstruct) ā¢ š Paper ā¢ š Project Page
äøęē(Chinese)
AgentTuning represents the very first attempt to instruction-tune LLMs using interaction trajectories across multiple agent tasks. Evaluation results indicate that AgentTuning enables the agent capa... See more
THUDM ā¢ GitHub - THUDM/AgentTuning: AgentTuning: Enabling Generalized Agent Abilities for LLMs
Nicolay Gerold added