Instructions to use hf-internal-testing/tiny-random-RemBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RemBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-RemBertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RemBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-RemBertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-RemBertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 18.2 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-RemBertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-RemBertForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-RemBertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
18.2 MB
- Xet hash:
- 73ab8f500de1ed30d871fd998932838911c396838f91a91cfc9036274ef6912b
- Size of remote file:
- 18.2 MB
- SHA256:
- 846d07c9ad6ea9efa48a4deb11dea71ab1130dffdb577913ce9306bd612839c3
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