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 heads.json from jensilo/acclass: direct link, hf CLI and curl.
- Browser
- Download file 174 Bytes
-
https://huggingface.co/jensilo/acclass/resolve/main/heads.json
- Command line
-
hf download hf://jensilo/acclass/heads.json
-
curl -L -o heads.json https://huggingface.co/jensilo/acclass/resolve/main/heads.json
174 Bytes
| ["local_state_change","outbound","egress","remote_state_change","delegated_execution","exposes_secrets","destructive","host_control_change","fetched_or_generated_execution"] | |