Instructions to use hf-internal-testing/explicit_transformers_weight_in_config with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/explicit_transformers_weight_in_config with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/explicit_transformers_weight_in_config")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/explicit_transformers_weight_in_config") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/explicit_transformers_weight_in_config") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
CHANGED
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@@ -22,5 +22,5 @@
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"type_vocab_size": 16,
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"use_cache": true,
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"vocab_size": 1124,
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-
"transformers_weights": "transformers.safetensors
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}
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"type_vocab_size": 16,
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"use_cache": true,
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"vocab_size": 1124,
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+
"transformers_weights": "transformers.safetensors"
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}
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