Huggingface ppl
Web30 sep. 2024 · huggingface / transformers Public Notifications Fork 19.2k Star 90.3k Code Issues 509 Pull requests 140 Actions Projects 25 Security Insights New issue Weird behavior of BertLMHeadModel and RobertaForCausalLM #13818 Closed 2 tasks done veronica320 opened this issue on Sep 30, 2024 · 4 comments veronica320 commented … Web8 mrt. 2024 · The ppl of GPT2 is strangely high. Is there anything that needs to be modified when testing finetuned-gpt2 with convai_evalution.py? I'm also curious about the best test results and hyperparameters when you finetuned from GPT2.
Huggingface ppl
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Web3 aug. 2024 · Huggingface Best Readme Template License Distributed under the MIT License. See LICENSE for more information. Citing & Authors If you find this repository helpful, feel free to cite our publication Fine-grained controllable text generation via Non-Residual Prompting: Web10 jul. 2024 · Hmm yes, you should actually divide by encodings.input_ids.size(1) since i doesn’t account for the length of the last stride.. I also just spotted another bug. When …
Web6 apr. 2024 · The Hugging Face Hub is a platform with over 90K models, 14K datasets, and 12K demos in which people can easily collaborate in their ML workflows. The Hub works … WebPerplexity (PPL) is one of the most common metrics for evaluating language models. It is defined as the exponentiated average negative log-likelihood of a sequence, calculated …
WebOverview The T5 model was presented in Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer by Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu.. The abstract from the paper is the following: Transfer learning, where a model is first pre-trained on a data … WebHugging Face’s complete ecosystem in your private, compliant environment 1. Experiment Leverage +55,000 models and +6,000 datasets publicly available in our Hub. Test …
Web10 apr. 2024 · In recent years, pretrained models have been widely used in various fields, including natural language understanding, computer vision, and natural language generation. However, the performance of these language generation models is highly dependent on the model size and the dataset size. While larger models excel in some …
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