Instructions to use tliumozilla/mobilebert-query-intent-detection-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tliumozilla/mobilebert-query-intent-detection-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tliumozilla/mobilebert-query-intent-detection-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tliumozilla/mobilebert-query-intent-detection-test") model = AutoModelForSequenceClassification.from_pretrained("tliumozilla/mobilebert-query-intent-detection-test") - Notebooks
- Google Colab
- Kaggle
Commit ·
8d435ca
1
Parent(s): 0fbcc5b
upload v3.2
Browse files- config.json +4 -4
- label_map.json +10 -0
- model.safetensors +1 -1
config.json
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"hidden_dropout_prob": 0.0,
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"hidden_size": 512,
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"id2label": {
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"0": "
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"1": "
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},
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"initializer_range": 0.02,
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"intermediate_size": 512,
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"intra_bottleneck_size": 128,
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"key_query_shared_bottleneck": true,
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"label2id": {
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"Chat":
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"Search":
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"hidden_dropout_prob": 0.0,
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"hidden_size": 512,
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"id2label": {
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"0": "Chat",
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"1": "Search"
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},
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"initializer_range": 0.02,
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"intermediate_size": 512,
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"intra_bottleneck_size": 128,
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"key_query_shared_bottleneck": true,
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"label2id": {
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"Chat": 0,
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"Search": 1
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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label_map.json
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{
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"label2id": {
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"Chat": 0,
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"Search": 1
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},
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"id2label": {
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"0": "Chat",
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"1": "Search"
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}
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 98470112
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version https://git-lfs.github.com/spec/v1
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oid sha256:576c48487aa4382dd7ba85b51363b5c16783db47d7ec210632b97f8cc1446683
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size 98470112
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