Instructions to use canIjoin/datafun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use canIjoin/datafun with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="canIjoin/datafun")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("canIjoin/datafun") model = AutoModelForTokenClassification.from_pretrained("canIjoin/datafun", device_map="auto") - Notebooks
- Google Colab
- Kaggle
update config.json
Browse files- config.json +1 -1
config.json
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@@ -16,7 +16,7 @@
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"label2id": {
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"B-LOC": 1,
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"I-LOC": 2,
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"0":
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},
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"layer_norm_eps": 1e-12,
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"max_LOC_embeddings": 512,
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"label2id": {
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"B-LOC": 1,
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"I-LOC": 2,
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"0": 0
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},
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"layer_norm_eps": 1e-12,
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"max_LOC_embeddings": 512,
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