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YAML Metadata Error: "datasets[0]" with value "mC4 Japanese" is not valid. If possible, use a dataset id from https://hf.co/datasets. roberta-long-japanese (jumanpp + sentencepiece, mC4 Japanese) This is the longer input version of RoBERTa Japanese model pretrained on approximately 200M Japanese sentences. max_position_embeddings has been increased to 1282, allowing it to handle much longer inputs
Discover amazing ML apps made by the community
Additionally, you can use SequentialEvaluator to combine multiple evaluators into one, which can then be passed to the SentenceTransformerTrainer. If you don't have the necessary evaluation data but still want to track the model's performance on common benchmarks, you can use these evaluators with data from Hugging Face: EmbeddingSimilarityEvaluator with STSb The STS Benchmark (a.k.a. STSb) is a c
Finding the right Vision Language Model There are many ways to select the most appropriate model for your use case. Vision Arena is a leaderboard solely based on anonymous voting of model outputs and is updated continuously. In this arena, the users enter an image and a prompt, and outputs from two different models are sampled anonymously, then the user can pick their preferred output. This way, t
","cls_token":"","eos_token":"","mask_token":"","pad_token":"","sep_token":"","unk_token":""}},"createdAt":"2024-03-15T13:32:18.000Z","discussionsDisabled":false,"downloads":473434,"downloadsAllTime":3298501,"id":"BAAI/bge-reranker-v2-m3","isLikedByUser":false,"isWatchedByUser":false,"inference":"pipeline-library-pair-not-supported","lastModified":"2024-06-24T14:08:45.000Z","likes":247,"pipeline_t
Improving scalability There are several ways to approach the challenges of scaling embeddings. The most common approach is dimensionality reduction, such as PCA. However, classic dimensionality reduction -- like PCA methods -- tends to perform poorly when used with embeddings. In recent news, Matryoshka Representation Learning (blogpost) (MRL) as used by OpenAI also allows for cheaper embeddings.
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