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@@ -12,6 +12,7 @@ license: apache-2.0
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  short_description: All olaverse language-identification models in one Space
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  models:
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  - olaverse/lid-neural-5
 
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  - olaverse/lid-lite-25
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  - olaverse/lid-neural-25.1
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  - olaverse/lid-neural-25.2
@@ -22,10 +23,11 @@ models:
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  All language-identification models published under [olaverse](https://huggingface.co/olaverse), in one Space:
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  - **[lid-neural-5](https://huggingface.co/olaverse/lid-neural-5)** — Nigerian-focused, 4 languages (Yoruba, Hausa, Igbo, Nigerian Pidgin)
 
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  - **[lid-lite-25](https://huggingface.co/olaverse/lid-lite-25)** — fastText, CPU-only, 25 languages
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  - **[lid-neural-25.1](https://huggingface.co/olaverse/lid-neural-25.1)** — XLM-R, 25 languages, tuned for passages
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  - **[lid-neural-25.2](https://huggingface.co/olaverse/lid-neural-25.2)** — XLM-R, 25 languages, tuned for short queries
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- Pick a single model to test, or run text through all four at once to compare. Only one model is kept in memory at a time to stay within hardware quota.
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  short_description: All olaverse language-identification models in one Space
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  models:
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  - olaverse/lid-neural-5
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+ - olaverse/lid-neural-5.1
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  - olaverse/lid-lite-25
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  - olaverse/lid-neural-25.1
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  - olaverse/lid-neural-25.2
 
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  All language-identification models published under [olaverse](https://huggingface.co/olaverse), in one Space:
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  - **[lid-neural-5](https://huggingface.co/olaverse/lid-neural-5)** — Nigerian-focused, 4 languages (Yoruba, Hausa, Igbo, Nigerian Pidgin)
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+ - **[lid-neural-5.1](https://huggingface.co/olaverse/lid-neural-5.1)** — same 4 languages, sentence-level tuned on `mist-encoder-base-ng` (97.6% accuracy)
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  - **[lid-lite-25](https://huggingface.co/olaverse/lid-lite-25)** — fastText, CPU-only, 25 languages
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  - **[lid-neural-25.1](https://huggingface.co/olaverse/lid-neural-25.1)** — XLM-R, 25 languages, tuned for passages
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  - **[lid-neural-25.2](https://huggingface.co/olaverse/lid-neural-25.2)** — XLM-R, 25 languages, tuned for short queries
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+ Pick a single model to test, or run text through all five at once to compare. Only one model is kept in memory at a time to stay within hardware quota.
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference