Instructions to use dcarpintero/pangolin-guard-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dcarpintero/pangolin-guard-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dcarpintero/pangolin-guard-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dcarpintero/pangolin-guard-large") model = AutoModelForSequenceClassification.from_pretrained("dcarpintero/pangolin-guard-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from dcarpintero/pangolin-guard-large: direct link, hf CLI and curl.
- Browser
- Download file 1.48 kB
-
https://huggingface.co/dcarpintero/pangolin-guard-large/resolve/6f53a46c6dc11d3085bf5962069224f4391a4176/config.json
- Command line
-
hf download hf://dcarpintero/pangolin-guard-large@6f53a46c6dc11d3085bf5962069224f4391a4176/config.json
-
curl -L -o config.json https://huggingface.co/dcarpintero/pangolin-guard-large/resolve/6f53a46c6dc11d3085bf5962069224f4391a4176/config.json
1.48 kB
| { | |
| "_name_or_path": "answerdotai/ModernBERT-large", | |
| "architectures": [ | |
| "ModernBertForSequenceClassification" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 50281, | |
| "classifier_activation": "gelu", | |
| "classifier_bias": false, | |
| "classifier_dropout": 0.0, | |
| "classifier_pooling": "mean", | |
| "cls_token_id": 50281, | |
| "decoder_bias": true, | |
| "deterministic_flash_attn": false, | |
| "embedding_dropout": 0.0, | |
| "eos_token_id": 50282, | |
| "global_attn_every_n_layers": 3, | |
| "global_rope_theta": 160000.0, | |
| "gradient_checkpointing": false, | |
| "hidden_activation": "gelu", | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "safe", | |
| "1": "unsafe" | |
| }, | |
| "initializer_cutoff_factor": 2.0, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 2624, | |
| "label2id": { | |
| "safe": "0", | |
| "unsafe": "1" | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "local_attention": 128, | |
| "local_rope_theta": 10000.0, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "mlp_dropout": 0.0, | |
| "model_type": "modernbert", | |
| "norm_bias": false, | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 28, | |
| "pad_token_id": 50283, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "reference_compile": true, | |
| "repad_logits_with_grad": false, | |
| "sep_token_id": 50282, | |
| "sparse_pred_ignore_index": -100, | |
| "sparse_prediction": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.48.3", | |
| "vocab_size": 50368 | |
| } | |