How to use hf-tiny-model-private/tiny-random-FNetForSequenceClassification 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-FNetForSequenceClassification")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FNetForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-FNetForSequenceClassification", device_map="auto")
https://huggingface.co/hf-tiny-model-private/tiny-random-FNetForSequenceClassification/resolve/ec6d31636591ed56928425781b7a08060143c8e0/tokenizer.json
hf download hf://hf-tiny-model-private/tiny-random-FNetForSequenceClassification@ec6d31636591ed56928425781b7a08060143c8e0/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/hf-tiny-model-private/tiny-random-FNetForSequenceClassification/resolve/ec6d31636591ed56928425781b7a08060143c8e0/tokenizer.json
