Instructions to use Shaer-AI-2/Shaer-adapters-grpo-short1k-no-trio-v4 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-short1k-no-trio-v4 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Shaer-AI-2/Shaer-adapters-grpo-short1k-no-trio-v4", 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": 9955, | |
| "eval_size": 80, | |
| "test_size": 80, | |
| "hard_diagnostic_size": 3126, | |
| "phase1_max_bayts": "20", | |
| "allowed_meters": [], | |
| "train_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_easyfirst_short_drop_trio/cap_1000/selected_manifest.csv", | |
| "hard_diagnostic_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_easyfirst_short_drop_trio/hard_diagnostic_cap_256/selected_manifest.csv", | |
| "eval_bank_per_meter_per_bucket": 4, | |
| "test_bank_per_meter_per_bucket": 4, | |
| "eval_allowed_length_buckets": [ | |
| "1-3", | |
| "4-6" | |
| ], | |
| "eval_drop_meters": [ | |
| "المديد", | |
| "المنسرح", | |
| "الهزج" | |
| ], | |
| "train_length_bucket_counts": { | |
| "1-3": 6983, | |
| "4-6": 2972 | |
| }, | |
| "eval_length_bucket_counts": { | |
| "1-3": 40, | |
| "4-6": 40 | |
| }, | |
| "hard_diagnostic_length_bucket_counts": { | |
| "1-3": 683, | |
| "4-6": 746, | |
| "7-10": 658, | |
| "11-20": 1039 | |
| }, | |
| "train_base_meter_counts": { | |
| "البسيط": 1000, | |
| "الخفيف": 1000, | |
| "الرجز": 1000, | |
| "الرمل": 1000, | |
| "السريع": 1000, | |
| "الطويل": 1000, | |
| "الكامل": 1000, | |
| "المتقارب": 1000, | |
| "المجتث": 955, | |
| "الوافر": 1000 | |
| }, | |
| "eval_base_meter_counts": { | |
| "البسيط": 8, | |
| "الخفيف": 8, | |
| "الرجز": 8, | |
| "الرمل": 8, | |
| "السريع": 8, | |
| "الطويل": 8, | |
| "الكامل": 8, | |
| "المتقارب": 8, | |
| "المجتث": 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 | |
| } | |
| } |