Text Classification
Transformers
ONNX
Safetensors
GGUF
Transformers.js
English
modernbert
shell
security
coding-agents
multi-label-classification
text-embeddings-inference
Instructions to use jensilo/acclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jensilo/acclass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jensilo/acclass")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jensilo/acclass") model = AutoModelForSequenceClassification.from_pretrained("jensilo/acclass", device_map="auto") - Transformers.js
How to use jensilo/acclass with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'jensilo/acclass'); - Notebooks
- Google Colab
- Kaggle
Download config.json from jensilo/acclass: direct link, hf CLI and curl.
- Browser
- Download file 2.51 kB
-
https://huggingface.co/jensilo/acclass/resolve/main/config.json
- Command line
-
hf download hf://jensilo/acclass/config.json
-
curl -L -o config.json https://huggingface.co/jensilo/acclass/resolve/main/config.json
2.51 kB
| { | |
| "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, | |
| "dtype": "float32", | |
| "embedding_dropout": 0.0, | |
| "eos_token_id": 50282, | |
| "global_attn_every_n_layers": 3, | |
| "gradient_checkpointing": false, | |
| "hidden_activation": "gelu", | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "local_state_change", | |
| "1": "outbound", | |
| "2": "egress", | |
| "3": "remote_state_change", | |
| "4": "delegated_execution", | |
| "5": "exposes_secrets", | |
| "6": "destructive", | |
| "7": "host_control_change", | |
| "8": "fetched_or_generated_execution" | |
| }, | |
| "initializer_cutoff_factor": 2.0, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1152, | |
| "label2id": { | |
| "delegated_execution": 4, | |
| "destructive": 6, | |
| "egress": 2, | |
| "exposes_secrets": 5, | |
| "fetched_or_generated_execution": 8, | |
| "host_control_change": 7, | |
| "local_state_change": 0, | |
| "outbound": 1, | |
| "remote_state_change": 3 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "layer_types": [ | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention" | |
| ], | |
| "local_attention": 128, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "mlp_dropout": 0.0, | |
| "model_type": "modernbert", | |
| "norm_bias": false, | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 22, | |
| "pad_token_id": 50283, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "multi_label_classification", | |
| "rope_parameters": { | |
| "full_attention": { | |
| "rope_theta": 160000.0, | |
| "rope_type": "default" | |
| }, | |
| "sliding_attention": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| } | |
| }, | |
| "sep_token_id": 50282, | |
| "sparse_pred_ignore_index": -100, | |
| "sparse_prediction": false, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.1.0", | |
| "vocab_size": 50368 | |
| } | |