Instructions to use SkillScreen/SkillScreen-2B-Package-Experimental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkillScreen/SkillScreen-2B-Package-Experimental with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SkillScreen/SkillScreen-2B-Package-Experimental")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("SkillScreen/SkillScreen-2B-Package-Experimental") model = AutoModelForSequenceClassification.from_pretrained("SkillScreen/SkillScreen-2B-Package-Experimental", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download merge_verification.json from SkillScreen/SkillScreen-2B-Package-Experimental: direct link, hf CLI and curl.
- Browser
- Download file 1.2 kB
-
https://huggingface.co/SkillScreen/SkillScreen-2B-Package-Experimental/resolve/main/merge_verification.json
- Command line
-
hf download hf://SkillScreen/SkillScreen-2B-Package-Experimental/merge_verification.json
-
curl -L -o merge_verification.json https://huggingface.co/SkillScreen/SkillScreen-2B-Package-Experimental/resolve/main/merge_verification.json
1.2 kB
| { | |
| "passed": true, | |
| "run_id": "package-sbr-s42-r001", | |
| "seed": 42, | |
| "selected_update": 180, | |
| "precision": "bfloat16", | |
| "threshold": 0.5, | |
| "validation_records": 403, | |
| "longest_validation_tokens": 32768, | |
| "original_adapter_replay_max_logit_difference": 0.0625, | |
| "original_adapter_replay_max_probability_difference": 9.477205614150108e-05, | |
| "original_adapter_replay_decision_differences_at_0_5": 0, | |
| "fresh_native_reload_max_logit_difference": 0.0, | |
| "trained_classification_head_preserved": true, | |
| "merge_max_logit_difference": 0.140625, | |
| "merge_max_probability_difference": 0.006252712940063354, | |
| "decision_differences_at_0_5": 0, | |
| "adapter_validation_at_0_5": { | |
| "tp": 247, | |
| "fn": 2, | |
| "fp": 1, | |
| "tn": 153, | |
| "recall": 0.9919678714859438, | |
| "fpr": 0.006493506493506494 | |
| }, | |
| "merged_validation_at_0_5": { | |
| "tp": 247, | |
| "fn": 2, | |
| "fp": 1, | |
| "tn": 153, | |
| "recall": 0.9919678714859438, | |
| "fpr": 0.006493506493506494 | |
| }, | |
| "peak_gpu_allocated_gib": 7.92598819732666, | |
| "peak_gpu_reserved_gib": 8.2578125, | |
| "seconds": 294.2033534530201, | |
| "public_scoring_helper": { | |
| "passed": true, | |
| "probability_difference": 0.0, | |
| "used_tokens": 32768 | |
| } | |
| } | |