Text Classification
Transformers
Safetensors
Laya
system-one
calibrated-decisions
rlcd
classification
routing
scoring
guardrails
moderation
reinforcement-learning
commercial-use
Instructions to use GeekyAbs/laya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GeekyAbs/laya with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GeekyAbs/laya")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GeekyAbs/laya", device_map="auto") - Laya
How to use GeekyAbs/laya with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 2,976 Bytes
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"model": "rl-agent",
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},
"by_task_family": {
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"email triage": {
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"instruction-following tasks": {
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},
"intent and routing": {
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"moderation and safety": {
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"reading comprehension": {
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"response quality scoring": {
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"search relevance": {
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"moderation and safety": {
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}
},
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"latency_ms": {
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"p95_ms": 42.1
},
"10_questions": {
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},
"50_questions": {
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}
},
"act_policy": {
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"accuracy_when_escalating": null,
"accuracy_all": 0.8032331136738056
}
}
} |