Model overview
This is a IndicSBERT model ( l3cube-pune/indic-sentence-bert-nli ) trained on the STS dataset of ten major Indian Languages. The single model works for English, Hindi, Marathi, Kannada, Tamil, Telugu, Gujarati, Oriya, Punjabi, Malayalam, and Bengali. The model also has cross-lingual capabilities. Released as a part of project MahaNLP: https://github.com/l3cube-pune/MarathiNLP Generic Indic Sentence BERT model is shared here : l3cube-pune/indic-sentence-bert-nli More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2304.11434) Other Monolingual similarity models are listed below: Marathi Similarity Hindi Similarity Kannada Similarity Telugu Similarity Malayalam Similarity Tamil Similarity Gujarati Similarity Oriya Similarity Bengali Similarity Punjabi Similarity Indic Similarity (multilingual)
Key features
特点摘要待依据来源补齐,不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
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Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证:cc-by-4.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。