Instructions to use junzai/ai12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junzai/ai12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="junzai/ai12")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junzai/ai12") model = AutoModelForMaskedLM.from_pretrained("junzai/ai12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from junzai/ai12: direct link, hf CLI and curl.
- Browser
- Download file 777 Bytes
-
https://huggingface.co/junzai/ai12/resolve/main/config.json
- Command line
-
hf download hf://junzai/ai12/config.json
-
curl -L -o config.json https://huggingface.co/junzai/ai12/resolve/main/config.json
777 Bytes
| { | |
| "architectures": [ | |
| "BertForMaskedLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "finetuning_task": "mrpc", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "num_labels": 2, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pruned_heads": {}, | |
| "torchscript": false, | |
| "type_vocab_size": 2, | |
| "use_bfloat16": false, | |
| "vocab_size": 30522 | |
| } | |