verdict-small
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Weaver (alpha)
mancerAn attempt to recreate Claude-style verbosity, but don't expect the same level of coherence or memory. Meant for use in roleplay/narrative situations.
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$0.4 / M input tokensOpenRouter · mancer/weaver
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ManelThis is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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View details ↗chrono-bert-v1-19991231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20061231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20091231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20101231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20111231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20131231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20141231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20151231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20161231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20171231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20181231
manelalabChronoBERT is a series of **high-performance chronologically consistent large language models (LLM)** designed to eliminate lookahead bias and training leakage while maintaining good language understanding in time-sensitive applications. The model is pretrained on **diverse, high-quality, open-source, and timestamped text** to maintain chronological consistency. All models in the series achieve **GLUE benchmark scores that surpass standard BERT.** This approach preserves the integrity of historical analysis and enables more reliable economic and financial modeling. The following contains a code snippet illustrating how to use the model to generate embeddings based on given inputs.
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View details ↗chrono-bert-v1-20191231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20201231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20211231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20221231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20231231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chrono-bert-v1-20241231
manelalab基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗tta1
mangasla基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗CharHelper
ManglerFTW基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗> ⚠️ **Mirror-only**: 数据已迁移到正确的 **dataset 类型仓库**，请优先使用： > 👉 **https://huggingface.co/datasets/MangoGoes/libero4in1_wan2.2vae_latent_dataset** > > 本仓库（`repo_type='model'`）保留作为镜像，文件内容完全一致。下载时建议从 dataset 仓库拉，可享受 dataset viewer / parquet 流式预览等特性。 LIBERO 4in1（libero_spatial / libero_object / libero_goal / libero_10）共 53.19 GB 的 Wan2.2-VAE 编码 latent 缓存：
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View details ↗flux2-klein-4b-gguf
manishdashsharma基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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