How to use hf-internal-testing/tiny-random-FNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FNetModel")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FNetModel", device_map="auto")
https://huggingface.co/hf-internal-testing/tiny-random-FNetModel/resolve/48fa66de37df126504db3b658806135eb877f505/tokenizer.json
hf download hf://hf-internal-testing/tiny-random-FNetModel@48fa66de37df126504db3b658806135eb877f505/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-FNetModel/resolve/48fa66de37df126504db3b658806135eb877f505/tokenizer.json
