ExpertPrompting: Instructing Large Language Models to be Distinguished Experts(Xu et al., 2023) MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework(Hong et al., 2023) Meta Prompting for AGI Systems(Zhang, 2023) On Meta-Prompting(de Wynter et a., 2023) ...
num_return_sequences=1,eos_token_id=tokenizer.eos_token_id,max_length=200,)forseqinsequences:pr...
5 DeepLearning.AI, “Agentic Design Patterns Part 5, Multi-Agent Collaboration Prompting an LLM to Play Different Roles for Different Parts of a Complex Task Summons a Team of AI Agents That Can Do the Job More Effectively.,” Agentic Design Patterns Part 5, Multi-Agent Collaboration, https:...
Llama 3.1 family of models. Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability. Model Release Date:July 23, 2024. Status:This is a static model trained on an offline dataset. Future versions of the tuned models...
For further information, please see the llamafile README. Having trouble? See the "Gotchas" section of the README. Prompting Prompt template: <|begin_of_text|><|start_header_id|>system<|end_header_id|> {{prompt}}<|eot_id|>{{history}}<|start_header_id|>{{char}}<|end_header_id|...
Techniques like “chain-of-thought” prompting and self-consistency decoding have already been used to improve LLM reasoning in research (论文阅读:Self-Consistency Improves Chain of Thought Reasoning ...). In fact, one self-consistency approach has the model generate multiple reasoning paths and ...
Therefore, open-source AI platforms are necessary. The crisis I see in Europe and elsewhere is that geopolitical competition is prompting some governments to essentially declare the release of open-source models illegal because they want to keep scientific secrets to maintain their lead. This is a...
For both scenarios, we conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature...
For both scenarios, we conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature...
"SAM-SP: Self-Prompting Makes SAM Great Again." ArXiv (2024). [paper] [2024.08] 💥GSAM:Sota Kato, Hinako Mitsuoka, Kazuhiro Hotta. "Generalized SAM: Efficient Fine-Tuning of SAM for Variable Input Image Sizes." ECCVW (2024). [paper] [2024.08] ...