Text Classification
Transformers
PyTorch
Safetensors
bert
voicemail-detection
text-embeddings-inference
Instructions to use Adya662/bert-tiny-amd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adya662/bert-tiny-amd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Adya662/bert-tiny-amd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Adya662/bert-tiny-amd") model = AutoModelForSequenceClassification.from_pretrained("Adya662/bert-tiny-amd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Adya662/bert-tiny-amd: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/Adya662/bert-tiny-amd/resolve/main/model.safetensors
- Command line
-
hf download hf://Adya662/bert-tiny-amd/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Adya662/bert-tiny-amd/resolve/main/model.safetensors
17.5 MB
- Xet hash:
- 8109c192fe6668bebabbe2df82edf5c0881d14d516ab8709756c5e4c0fcbbb1f
- Size of remote file:
- 17.5 MB
- SHA256:
- 7b6694c3a800b01632ff33191bd8a12d4e0d0376fc82f8c509743e7a55f94bec
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