Instructions to use Tatiana239/lilt-ruroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tatiana239/lilt-ruroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tatiana239/lilt-ruroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tatiana239/lilt-ruroberta") model = AutoModelForTokenClassification.from_pretrained("Tatiana239/lilt-ruroberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
bc8672f
1
Parent(s): c160bac
Training in progress, step 2
Browse files- config.json +38 -14
- logs/1674140549.3868175/events.out.tfevents.1674140549.pc092u.2747800.1 +3 -0
- logs/1674141391.9281697/events.out.tfevents.1674141391.pc092u.2747949.1 +3 -0
- logs/1674184435.5003195/events.out.tfevents.1674184435.pc092u.2748676.1 +3 -0
- logs/1674186463.1699555/events.out.tfevents.1674186463.pc092u.2749881.1 +3 -0
- logs/1674188656.4764483/events.out.tfevents.1674188656.pc092u.2750066.1 +3 -0
- logs/events.out.tfevents.1674140449.pc092u.2747376.0 +2 -2
- logs/events.out.tfevents.1674140549.pc092u.2747800.0 +3 -0
- logs/events.out.tfevents.1674141391.pc092u.2747949.0 +3 -0
- logs/events.out.tfevents.1674184435.pc092u.2748676.0 +3 -0
- logs/events.out.tfevents.1674186463.pc092u.2749881.0 +3 -0
- logs/events.out.tfevents.1674188656.pc092u.2750066.0 +3 -0
- pytorch_model.bin +2 -2
config.json
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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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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"layer_norm_eps": 1e-05,
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"max_2d_position_embeddings": 1024,
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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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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"B-Comment": 10,
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"O": 9
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},
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"layer_norm_eps": 1e-05,
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"max_2d_position_embeddings": 1024,
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pytorch_model.bin
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