Instructions to use mrsteyk/flan-ul2-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrsteyk/flan-ul2-encoder with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mrsteyk/flan-ul2-encoder") model = AutoModel.from_pretrained("mrsteyk/flan-ul2-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from mrsteyk/flan-ul2-encoder: direct link, hf CLI and curl.
- Browser
- Download file 766 Bytes
-
https://huggingface.co/mrsteyk/flan-ul2-encoder/resolve/main/config.json
- Command line
-
hf download hf://mrsteyk/flan-ul2-encoder/config.json
-
curl -L -o config.json https://huggingface.co/mrsteyk/flan-ul2-encoder/resolve/main/config.json
766 Bytes
| { | |
| "_name_or_path": "google/flan-ul2", | |
| "architectures": [ | |
| "T5EncoderModel" | |
| ], | |
| "classifier_dropout": 0.0, | |
| "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": "4.35.1", | |
| "use_cache": true, | |
| "vocab_size": 32128 | |
| } | |