Text Classification
Transformers
Safetensors
Chinese
laya
system-one
calibrated-decisions
rlcd
chinese
classification
routing
scoring
guardrails
non-autoregressive
commercial-license-required
Instructions to use ZichenAI/layazh-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZichenAI/layazh-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZichenAI/layazh-zh")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZichenAI/layazh-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
NovaAI
layazh-zh: Chinese System-1 decision model (Laya recipe, RoBERTa-large encoder + decision head); full-eval acc 0.6951 vs upstream 0.4783
f69ec12 verified Download encoder/config.json from ZichenAI/layazh-zh: direct link, hf CLI and curl.
- Browser
- Download file 920 Bytes
-
https://huggingface.co/ZichenAI/layazh-zh/resolve/main/encoder/config.json
- Command line
-
hf download hf://ZichenAI/layazh-zh/encoder/config.json
-
curl -L -o config.json https://huggingface.co/ZichenAI/layazh-zh/resolve/main/encoder/config.json
920 Bytes
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForMaskedLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "directionality": "bidi", | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "is_decoder": false, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.17.0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 21128 | |
| } | |