Text Classification
Transformers
ONNX
Safetensors
Transformers.js
bert
eu-ai-act
ai-governance
legal
devseis
research-note
text-embeddings-inference
Instructions to use Devseis/devseis-ai-act-classifier-v6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devseis/devseis-ai-act-classifier-v6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Devseis/devseis-ai-act-classifier-v6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Devseis/devseis-ai-act-classifier-v6") model = AutoModelForSequenceClassification.from_pretrained("Devseis/devseis-ai-act-classifier-v6", device_map="auto") - Transformers.js
How to use Devseis/devseis-ai-act-classifier-v6 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-classification', 'Devseis/devseis-ai-act-classifier-v6'); - Notebooks
- Google Colab
- Kaggle
Claude Opus 5.5
Devseis AI Act Classifier v6: weights, int8 ONNX, card and evaluation
7c594f6 verified Download evaluation/threshold.json from Devseis/devseis-ai-act-classifier-v6: direct link, hf CLI and curl.
- Browser
- Download file 2.52 kB
-
https://huggingface.co/Devseis/devseis-ai-act-classifier-v6/resolve/main/evaluation/threshold.json
- Command line
-
hf download hf://Devseis/devseis-ai-act-classifier-v6/evaluation/threshold.json
-
curl -L -o threshold.json https://huggingface.co/Devseis/devseis-ai-act-classifier-v6/resolve/main/evaluation/threshold.json
2.52 kB
| { | |
| "target": 0.9, | |
| "threshold": 0.5, | |
| "validation": [ | |
| { | |
| "t": 0.3, | |
| "answered": 1.0, | |
| "acc_answered": 0.846, | |
| "errors_flagged": "0/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.35, | |
| "answered": 1.0, | |
| "acc_answered": 0.846, | |
| "errors_flagged": "0/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.4, | |
| "answered": 0.988, | |
| "acc_answered": 0.844, | |
| "errors_flagged": "0/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.45, | |
| "answered": 0.988, | |
| "acc_answered": 0.844, | |
| "errors_flagged": "0/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.5, | |
| "answered": 0.981, | |
| "acc_answered": 0.849, | |
| "errors_flagged": "1/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.55, | |
| "answered": 0.975, | |
| "acc_answered": 0.854, | |
| "errors_flagged": "2/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.6, | |
| "answered": 0.938, | |
| "acc_answered": 0.855, | |
| "errors_flagged": "3/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.65, | |
| "answered": 0.901, | |
| "acc_answered": 0.856, | |
| "errors_flagged": "4/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.7, | |
| "answered": 0.858, | |
| "acc_answered": 0.871, | |
| "errors_flagged": "7/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.75, | |
| "answered": 0.809, | |
| "acc_answered": 0.87, | |
| "errors_flagged": "8/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.8, | |
| "answered": 0.753, | |
| "acc_answered": 0.869, | |
| "errors_flagged": "9/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.85, | |
| "answered": 0.698, | |
| "acc_answered": 0.867, | |
| "errors_flagged": "10/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.9, | |
| "answered": 0.574, | |
| "acc_answered": 0.86, | |
| "errors_flagged": "12/25", | |
| "severe_still_answered": 0 | |
| }, | |
| { | |
| "t": 0.95, | |
| "answered": 0.309, | |
| "acc_answered": 0.88, | |
| "errors_flagged": "19/25", | |
| "severe_still_answered": 0 | |
| } | |
| ], | |
| "note": "The pre-set rule (answered accuracy >= 0.90 on validation) found no threshold: this model's errors are mostly confident. Chosen with the product owner: flag only genuinely split predictions (top probability < 0.50).", | |
| "test_at_threshold": { | |
| "t": 0.5, | |
| "answered": 0.995, | |
| "acc_answered": 0.833, | |
| "errors_flagged": "0/35", | |
| "severe_still_answered": 0 | |
| } | |
| } |