Text Classification
Transformers
Safetensors
English
xlm-roberta
social-media
text-embeddings-inference
Instructions to use sharecreative/high-analytical-value-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sharecreative/high-analytical-value-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sharecreative/high-analytical-value-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sharecreative/high-analytical-value-v1") model = AutoModelForSequenceClassification.from_pretrained("sharecreative/high-analytical-value-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download threshold.json from sharecreative/high-analytical-value-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.35 kB
-
https://huggingface.co/sharecreative/high-analytical-value-v1/resolve/main/threshold.json
- Command line
-
hf download hf://sharecreative/high-analytical-value-v1/threshold.json
-
curl -L -o threshold.json https://huggingface.co/sharecreative/high-analytical-value-v1/resolve/main/threshold.json
1.35 kB
| { | |
| "threshold": 0.5, | |
| "rule": "predict HAV when P(HAV) >= threshold", | |
| "positive_label": "HAV", | |
| "max_seq_length": 256, | |
| "chosen": "manually", | |
| "updated": "2026-10-08", | |
| "tuned_threshold_info": { | |
| "threshold": 0.873214840888977, | |
| "rule": "predict HAV when P(HAV) >= threshold", | |
| "positive_label": "HAV", | |
| "recall_floor": 0.75, | |
| "tuned_on": "pooled out-of-fold predictions, 5-fold CV on all labelled data (n=14982)", | |
| "final_mode": "cv_full", | |
| "oof_pooled_at_threshold": { | |
| "precision": 0.8600739371534196, | |
| "recall": 0.7502418574653338, | |
| "f1": 0.8014123320702722, | |
| "f0.5": 0.8356080741326054, | |
| "roc_auc": 0.9286660504841191 | |
| }, | |
| "oof_pooled_at_0.5": { | |
| "precision": 0.8010415071220708, | |
| "recall": 0.8432763624637214, | |
| "f1": 0.8216165265886419, | |
| "f0.5": 0.8091466056067826, | |
| "roc_auc": 0.9286660504841191 | |
| }, | |
| "cv_fold_mean_at_threshold": { | |
| "precision": 0.8602713115017393, | |
| "recall": 0.7502417405318292, | |
| "f1": 0.8014351606206255, | |
| "f0.5": 0.8357112536510138, | |
| "roc_auc": 0.9305891130964014 | |
| }, | |
| "cv_fold_sd_at_threshold": { | |
| "precision": 0.01264469910857227, | |
| "recall": 0.004401753404119227, | |
| "f1": 0.0035358058313396264, | |
| "f0.5": 0.008582361435463492, | |
| "roc_auc": 0.004316468755994513 | |
| } | |
| } | |
| } |