The idea of the ethical reasoning dataset is not to erase specific content. It is designed to present additional thinking traces with an ethical grounding. So far, it is only a fraction of the available data. This…
There is this ethical reasoning dataset to teach models stable and predictable values: https://huggingface.co/datasets/Bachstelze/ethical_coconot_6... An Olmo-3-7B-Think model is adapted with it. In theory, it should…
The authors propose a novel approach where checklists are automatically generated to systematically assess and guide LLM outputs, ensuring more comprehensive and reliable evaluations by LLMs. E.g. it increases in the…
Why do we need vectors for search anyway? The results are often unrelated to the query. Aren't therefore exact matches better? One could also annotate the corpus with related tags and hypothetical questions, if we need…
E.g. adapters, inference optimization and more (multilingual) models like https://huggingface.co/CohereForAI/aya-101
What is the advantage of Ollama Python over huggingface?
What is the point in using Ollama over huggingface if you use Python? Also, REST endpoints can be provided with huggingface transformer. Here with Go, it seems to make sense to use an abstraction. Though don't you lose…
This seems only to work cause large GPTs have redundant, undercomplex attentions. See this issue in BertViz about attention in Llama: https://github.com/jessevig/bertviz/issues/128
Those minified models are still equal or bigger compared to the initial "attention is all you need" transformer.
Have you also tried the bigger models? The smaller models are good for assisted generation: https://huggingface.co/blog/assisted-generation Those models of LaMini-Flan-T5 are trained to follow instructions and not to…
The idea of the ethical reasoning dataset is not to erase specific content. It is designed to present additional thinking traces with an ethical grounding. So far, it is only a fraction of the available data. This…
There is this ethical reasoning dataset to teach models stable and predictable values: https://huggingface.co/datasets/Bachstelze/ethical_coconot_6... An Olmo-3-7B-Think model is adapted with it. In theory, it should…
The authors propose a novel approach where checklists are automatically generated to systematically assess and guide LLM outputs, ensuring more comprehensive and reliable evaluations by LLMs. E.g. it increases in the…
Why do we need vectors for search anyway? The results are often unrelated to the query. Aren't therefore exact matches better? One could also annotate the corpus with related tags and hypothetical questions, if we need…
E.g. adapters, inference optimization and more (multilingual) models like https://huggingface.co/CohereForAI/aya-101
What is the advantage of Ollama Python over huggingface?
What is the point in using Ollama over huggingface if you use Python? Also, REST endpoints can be provided with huggingface transformer. Here with Go, it seems to make sense to use an abstraction. Though don't you lose…
This seems only to work cause large GPTs have redundant, undercomplex attentions. See this issue in BertViz about attention in Llama: https://github.com/jessevig/bertviz/issues/128
Those minified models are still equal or bigger compared to the initial "attention is all you need" transformer.
Have you also tried the bigger models? The smaller models are good for assisted generation: https://huggingface.co/blog/assisted-generation Those models of LaMini-Flan-T5 are trained to follow instructions and not to…