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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update config.json
Verified signaturec06b39b -
Update config.json
Verified signatured9ccfcc -
Upload BertForSequenceClassification
Verified signatureb521332
-
Update config.json
Verified signaturea9c08bf
-
Delete model.safetensors
Verified signature6f7715e -
Update config.json
Verified signaturea0b333f -
Upload transformers.safetensors
Verified signature71709f1
-
Upload model
Verified signature3a68aaa -
initial commit
Verified signatureb8979fd