Instructions to use Shaer-AI-2/Shaer-adapters-grpo-vnext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shaer-AI-2/Shaer-adapters-grpo-vnext with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Shaer-AI-2/Shaer-adapters-grpo-vnext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "dataset_id": "Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1", | |
| "dataset_source_id": "Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits", | |
| "train_dataset_id": "Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1", | |
| "source_dataset_id": "Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits", | |
| "train_split": "train", | |
| "eval_split": "eval", | |
| "test_split": "test", | |
| "train_size": 24897, | |
| "eval_size": 104, | |
| "test_size": 204, | |
| "hard_diagnostic_size": 3126, | |
| "phase1_max_bayts": "20", | |
| "allowed_meters": [], | |
| "train_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_drop_trio/cap_3000/selected_manifest.csv", | |
| "hard_diagnostic_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_drop_trio/hard_diagnostic_cap_256/selected_manifest.csv", | |
| "eval_bank_per_meter_per_bucket": 2, | |
| "test_bank_per_meter_per_bucket": 4, | |
| "train_length_bucket_counts": { | |
| "1-3": 16620, | |
| "4-6": 5092, | |
| "7-10": 1934, | |
| "11-20": 1251 | |
| }, | |
| "eval_length_bucket_counts": { | |
| "1-3": 26, | |
| "4-6": 26, | |
| "7-10": 26, | |
| "11-20": 26 | |
| }, | |
| "hard_diagnostic_length_bucket_counts": { | |
| "1-3": 683, | |
| "4-6": 746, | |
| "7-10": 658, | |
| "11-20": 1039 | |
| }, | |
| "train_base_meter_counts": { | |
| "البسيط": 3000, | |
| "الخفيف": 3000, | |
| "الرجز": 1901, | |
| "الرمل": 1760, | |
| "السريع": 2307, | |
| "الطويل": 3000, | |
| "الكامل": 3000, | |
| "المتقارب": 3000, | |
| "المجتث": 929, | |
| "الوافر": 3000 | |
| }, | |
| "eval_base_meter_counts": { | |
| "البسيط": 8, | |
| "الخفيف": 8, | |
| "الرجز": 8, | |
| "الرمل": 8, | |
| "السريع": 8, | |
| "الطويل": 8, | |
| "الكامل": 8, | |
| "المتقارب": 8, | |
| "المجتث": 8, | |
| "المديد": 8, | |
| "المنسرح": 8, | |
| "الهزج": 8, | |
| "الوافر": 8 | |
| }, | |
| "hard_diagnostic_base_meter_counts": { | |
| "البسيط": 256, | |
| "الخفيف": 256, | |
| "الرجز": 256, | |
| "الرمل": 256, | |
| "السريع": 256, | |
| "الطويل": 54, | |
| "الكامل": 256, | |
| "المتقارب": 256, | |
| "المجتث": 256, | |
| "المديد": 256, | |
| "المنسرح": 256, | |
| "الهزج": 256, | |
| "الوافر": 256 | |
| } | |
| } |