Text Classification
Safetensors
GLiClass
text classification
nli
sentiment analysis
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  GLiClass is an efficient zero-shot sequence classification model designed to achieve SoTA performance while being much faster than cross-encoders and LLMs, while preserving strong generalization capabilities.
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- The model supports text classification with any labels and can be used for the following tasks:
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  * Topic Classification
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  * Sentiment Analysis
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  * Intent Classification
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  See the [GLiClass library README](https://github.com/Knowledgator/GLiClass) for full details on these features.
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- ## GLiClass-V3 Models
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-
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- | Model | Size | Params | Avg Benchmark | Inference Speed (batch=1, A6000, ex/s) |
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- |-------|------|--------|---------------|----------------------------------------|
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- | [gliclass‑edge‑v3.0](https://huggingface.co/knowledgator/gliclass-edge-v3.0) | 131 MB | 32.7M | 0.4873 | 97.29 |
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- | [gliclass‑modern‑base‑v3.0](https://huggingface.co/knowledgator/gliclass-modern-base-v3.0) | 606 MB | 151M | 0.5571 | 54.46 |
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- | [gliclass‑modern‑large‑v3.0](https://huggingface.co/knowledgator/gliclass-modern-large-v3.0) | 1.6 GB | 399M | 0.6082 | 43.80 |
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- | [gliclass‑base‑v3.0](https://huggingface.co/knowledgator/gliclass-base-v3.0) | 746 MB | 187M | 0.6556 | 51.61 |
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- | [gliclass‑large‑v3.0](https://huggingface.co/knowledgator/gliclass-large-v3.0) | 1.75 GB | 439M | 0.7001 | 25.22 |
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-
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- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6405f62ba577649430be5124/MvfWyOdG824KWWB4Hy-dG.png)
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  ## Installation
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  F1 scores on zero-shot text classification (no fine-tuning on these datasets):
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  | Dataset | [large‑v3.0](https://huggingface.co/knowledgator/gliclass-large-v3.0) | [base‑v3.0](https://huggingface.co/knowledgator/gliclass-base-v3.0) | [modern‑large‑v3.0](https://huggingface.co/knowledgator/gliclass-modern-large-v3.0) | [modern‑base‑v3.0](https://huggingface.co/knowledgator/gliclass-modern-base-v3.0) | [edge‑v3.0](https://huggingface.co/knowledgator/gliclass-edge-v3.0) |
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  |---|---|---|---|---|---|
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  | CR | 0.9398 | 0.9127 | 0.8952 | 0.8902 | 0.8215 |
 
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  GLiClass is an efficient zero-shot sequence classification model designed to achieve SoTA performance while being much faster than cross-encoders and LLMs, while preserving strong generalization capabilities.
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+ The model supports text classification with any labels and can be used for **the following tasks:**
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  * Topic Classification
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  * Sentiment Analysis
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  * Intent Classification
 
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  See the [GLiClass library README](https://github.com/Knowledgator/GLiClass) for full details on these features.
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  ## Installation
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  F1 scores on zero-shot text classification (no fine-tuning on these datasets):
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+ GLiClass-V1 Multitask:
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+ | Dataset | [large‑v1.0](https://huggingface.co/knowledgator/gliclass-large-v1.0) | [base‑v1.0](https://huggingface.co/knowledgator/gliclass-base-v1.0) | [edge‑v1.0](https://huggingface.co/knowledgator/gliclass-edge-v1.0) |
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+ |---|---|---|---|
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+ | CR | 0.9066 | 0.8922 | 0.7661 |
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+ | sst2 | 0.9154 | 0.9198 | 0.6404 |
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+ | sst5 | 0.3387 | 0.2266 | 0.2372 |
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+ | 20_newsgroups | 0.5577 | 0.5189 | 0.2914 |
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+ | spam | 0.9790 | 0.9380 | 0.6692 |
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+ | financial_phrasebank | 0.8289 | 0.5217 | 0.3961 |
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+ | imdb | 0.9397 | 0.9364 | 0.8053 |
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+ | ag_news | 0.7521 | 0.6978 | 0.6202 |
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+ | emotion | 0.4473 | 0.4454 | 0.2686 |
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+ | cap_sotu | 0.4327 | 0.4579 | 0.2552 |
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+ | rotten_tomatoes | 0.8491 | 0.8458 | 0.4507 |
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+ | massive | 0.5824 | 0.4757 | 0.2360 |
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+ | banking | 0.6987 | 0.6072 | 0.4696 |
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+ | snips | 0.8509 | 0.6515 | 0.5369 |
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+ | **AVERAGE** | **0.7199** | **0.6525** | **0.4745** |
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+
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+ GLiClass-V3:
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  | Dataset | [large‑v3.0](https://huggingface.co/knowledgator/gliclass-large-v3.0) | [base‑v3.0](https://huggingface.co/knowledgator/gliclass-base-v3.0) | [modern‑large‑v3.0](https://huggingface.co/knowledgator/gliclass-modern-large-v3.0) | [modern‑base‑v3.0](https://huggingface.co/knowledgator/gliclass-modern-base-v3.0) | [edge‑v3.0](https://huggingface.co/knowledgator/gliclass-edge-v3.0) |
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  |---|---|---|---|---|---|
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  | CR | 0.9398 | 0.9127 | 0.8952 | 0.8902 | 0.8215 |