Search Results for "tensorflow" - Page 10
Sort By:
Showing 233 open source projects for "tensorflow"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Sales CRM and Pipeline Management Software | PipedrivePipedrive’s simple interface empowers salespeople to streamline workflows and unite sales tasks in one workspace. Unlock instant sales insights with Pipedrive’s visual sales pipeline and fine-tune your strategy with robust reporting features and a personalized AI Sales Assistant.
-
1
xlm-roberta-large
Large multilingual RoBERTa model trained on 100 languages
xlm-roberta-large is a multilingual transformer model pre-trained by Facebook AI on 2.5TB of filtered CommonCrawl data covering 100 languages. It is a large-sized version of XLM-RoBERTa, built on the RoBERTa architecture with enhanced multilingual capabilities. The model was trained using the masked language modeling (MLM) objective, where 15% of tokens are masked and predicted, enabling bidirectional context understanding. Unlike autoregressive models, it processes input holistically,... -
2
bert-base-cased
English BERT model using cased text for sentence-level tasks
bert-base-cased is a foundational transformer model pretrained on English using masked language modeling (MLM) and next sentence prediction (NSP). It is case-sensitive, treating "English" and "english" as distinct, making it suitable for tasks where casing matters. The model uses a bidirectional attention mechanism to deeply understand sentence structure, trained on BookCorpus and English Wikipedia. With 109M parameters and WordPiece tokenization (30K vocab size), it captures rich contextual... -
3
opt-125m
Compact GPT-style language model for open text generation and research
opt-125m is the smallest model in Meta AI’s OPT (Open Pre-trained Transformer) family—an open-source suite of decoder-only language models ranging from 125M to 175B parameters. It’s trained using causal language modeling (CLM), following similar architecture and objectives to GPT-3. The model was trained on 180B tokens from a diverse mix of datasets including BookCorpus, Common Crawl, Reddit, and more. OPT models aim to democratize access to large language models for responsible and... -
4
roberta-large
Large MLM-based English model optimized from BERT architecture
RoBERTa-large is a robustly optimized transformer model for English, trained by Facebook AI using a masked language modeling (MLM) objective. Unlike BERT, RoBERTa was trained on 160GB of data from BookCorpus, English Wikipedia, CC-News, OpenWebText, and Stories, with dynamic masking applied during training. It uses a byte-level BPE tokenizer and was trained with a sequence length of 512 and a batch size of 8K across 1024 V100 GPUs. RoBERTa improves performance across multiple NLP tasks by... -
Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
-
5
resnet50.a1_in1k
Zero-shot image-text classification with ViT-B/32 encoder.
clip-vit-base-patch32 is a zero-shot image classification model from OpenAI based on the CLIP (Contrastive Language–Image Pretraining) framework. It uses a Vision Transformer with base size and 32x32 patches (ViT-B/32) as the image encoder and a masked self-attention transformer as the text encoder. These components are jointly trained using contrastive loss to align images and text in a shared embedding space. The model excels in generalizing across tasks without additional fine-tuning by... -
6
bert-base-uncased
BERT-base-uncased is a foundational English model for NLP tasks
BERT-base-uncased is a 110-million-parameter English language model developed by Google, pretrained using masked language modeling and next sentence prediction on BookCorpus and English Wikipedia. It is case-insensitive and tokenizes text using WordPiece, enabling it to learn contextual relationships between words in a sentence bidirectionally. The model excels at feature extraction for downstream NLP tasks like sentence classification, named entity recognition, and question answering when... -
7
context_menu
A Python library to create and deploy cross-platform native context
A Python library to create and deploy cross-platform native context. context_menu was created as due to the lack of an intuitive and easy to use cross-platform context menu library. The library allows you to create your own context menu entries and control their behavior seamlessly in native Python code. It's fully documented and used by over 80,000 developers worldwide. -
8
Monk Computer Vision
A low code unified framework for computer vision and deep learning
Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
