Instructions to use hf-tiny-model-private/tiny-random-BertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-BertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-BertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-BertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 366 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-BertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-BertForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-BertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
366 kB
- Xet hash:
- 8dfcfd5c114bc1dd709557d74c68448cda25fb8293fae5f3c680545e983a64b7
- Size of remote file:
- 366 kB
- SHA256:
- 1d0063b0ebe2b8edff5ad1a681072fc569001a17e6ddd5c701baaa9d1b49dea5
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