Instructions to use google/ul2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/ul2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/ul2") model = AutoModelForSeq2SeqLM.from_pretrained("google/ul2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 748 Bytes
eeec07f | 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 28 29 30 31 32 | {
"_name_or_path": "ul2_model",
"architectures": [
"T5ForConditionalGeneration"
],
"d_ff": 16384,
"d_kv": 256,
"d_model": 4096,
"decoder_start_token_id": 0,
"dense_act_fn": "silu",
"dropout_rate": 0.1,
"eos_token_id": 1,
"feed_forward_proj": "gated-silu",
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"is_gated_act": true,
"layer_norm_epsilon": 1e-06,
"model_type": "t5",
"n_positions": 512,
"num_decoder_layers": 32,
"num_heads": 16,
"num_layers": 32,
"output_past": true,
"pad_token_id": 0,
"relative_attention_max_distance": 128,
"relative_attention_num_buckets": 32,
"torch_dtype": "bfloat16",
"transformers_version": "4.20.0.dev0",
"use_cache": true,
"vocab_size": 32128
}
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