Instructions to use zcharaf/FINBERX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zcharaf/FINBERX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zcharaf/FINBERX")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zcharaf/FINBERX") model = AutoModelForSequenceClassification.from_pretrained("zcharaf/FINBERX") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +6 -6
config.json
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@@ -10,16 +10,16 @@
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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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"0": "
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"1": "
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"2": "
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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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"
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"
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"
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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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"0": "Bearish",
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"1": "Bullish",
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"2": "Neutral"
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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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"Bearish": 0,
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"Bullish": 1,
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"Neutral": 2
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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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