Instructions to use google/fnet-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/fnet-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("google/fnet-large") model = AutoModelForPreTraining.from_pretrained("google/fnet-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 627 Bytes
ef91127 7753dca ef91127 8101480 ef91127 7753dca ef91127 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"actual_seq_length": 512,
"architectures": [
"FNetForPreTraining"
],
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "gelu_new",
"hidden_dropout_prob": 0.1,
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "fnet",
"num_hidden_layers": 24,
"pad_token_id": 3,
"torch_dtype": "float32",
"tpu_short_seq_length": 512,
"transformers_version": "4.10.0.dev0",
"type_vocab_size": 4,
"use_latest": false,
"use_fft": true,
"use_tpu_fourier_optimizations": false,
"vocab_size": 32000
}
|