Instructions to use SkillJev/SkillJev-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkillJev/SkillJev-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SkillJev/SkillJev-2B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("SkillJev/SkillJev-2B") model = AutoModelForSequenceClassification.from_pretrained("SkillJev/SkillJev-2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download export_provenance.json from SkillJev/SkillJev-2B: direct link, hf CLI and curl.
- Browser
- Download file 756 Bytes
-
https://huggingface.co/SkillJev/SkillJev-2B/resolve/main/export_provenance.json
- Command line
-
hf download hf://SkillJev/SkillJev-2B/export_provenance.json
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curl -L -o export_provenance.json https://huggingface.co/SkillJev/SkillJev-2B/resolve/main/export_provenance.json
756 Bytes
| { | |
| "run_id": "direct-r002", | |
| "selected_update": 426, | |
| "base_model": { | |
| "repo_id": "AlexWortega/openjev", | |
| "subfolder": "qwen3.5-2b-nli-v5", | |
| "revision": "a20448012c213128955ca0c693e7c943865cab77" | |
| }, | |
| "dataset": { | |
| "repo_id": "ProtectSkills/MaliciousSkillBench", | |
| "revision": "d4b42ce5766a6e0359c987cf59c1007cb3795a90", | |
| "config": "primary", | |
| "protocol": "source_balanced_random" | |
| }, | |
| "adapter_weights_sha256": "a065bd76fbdd1c89958937211d8b1e00c5ac5aad33dcefbd2c3e6e1551364131", | |
| "frozen_config_sha256": "36b443f390937d662107cfeb27df4ab09029aa7c21410f2ad6db4dfb52241425", | |
| "merge": "PEFT merge_and_unload(safe_merge=True)", | |
| "trained_classification_head_preserved": true, | |
| "precision": "bfloat16", | |
| "new_training": false | |
| } | |