Instructions to use hansgun/model_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hansgun/model_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hansgun/model_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hansgun/model_test") model = AutoModelForMaskedLM.from_pretrained("hansgun/model_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
modify label encoding
Browse files- config.json +4 -4
config.json
CHANGED
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@@ -8,14 +8,14 @@
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"
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"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"negative":
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"positive":
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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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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"LABEL_0": "negative",
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"LABEL_1": "positive"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"negative": "LABEL_0",
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"positive": "LABEL_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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