Instructions to use hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification 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-FlaubertForSequenceClassification 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-FlaubertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 8.97 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
8.97 MB
- Xet hash:
- 4af0aeaa033a977ef7f227cde56c9e890ca87859d69e5b1216b525d3641cc7ce
- Size of remote file:
- 8.97 MB
- SHA256:
- b564d5303c5ab0a60ef99d814752e2a56459e26578a2df4d000d4c718670a88d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.