Token Classification
Transformers
Safetensors
English
distilbert
named-entity-recognition
ner
bio
Eval Results (legacy)
Instructions to use Hasanblanka/polygraf-ner-stage3-first-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hasanblanka/polygraf-ner-stage3-first-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Hasanblanka/polygraf-ner-stage3-first-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Hasanblanka/polygraf-ner-stage3-first-model") model = AutoModelForTokenClassification.from_pretrained("Hasanblanka/polygraf-ner-stage3-first-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "stage": 3, | |
| "process": "fresh_process_cpu_inference_benchmark", | |
| "device": "cpu", | |
| "batch_size": 1, | |
| "warmup_batches": 5, | |
| "measured_batches": 100, | |
| "measured_sequences": 100, | |
| "measured_tokens_including_special": 9362, | |
| "elapsed_seconds": 5.222225, | |
| "sequences_per_second": 19.148927, | |
| "tokens_per_second": 1792.722588, | |
| "process_rss_before_bytes": 413868032, | |
| "process_peak_rss_bytes": 670052352, | |
| "incremental_peak_rss_bytes": 256184320, | |
| "parameter_count": 65203985, | |
| "model_directory_bytes": 261501138, | |
| "environment": { | |
| "python": "3.12.13", | |
| "platform": "Windows-11-10.0.26200-SP0", | |
| "processor": "Intel64 Family 6 Model 186 Stepping 2, GenuineIntel", | |
| "physical_cpu_cores": 8, | |
| "logical_cpu_cores": 12, | |
| "total_ram_bytes": 16890322944, | |
| "torch": "2.12.0+cpu", | |
| "transformers": "5.7.0", | |
| "huggingface_hub": "1.25.1", | |
| "numpy": "2.5.1", | |
| "scipy": "1.18.0", | |
| "scikit_learn": "1.9.0", | |
| "psutil": "7.2.2", | |
| "cuda_available": false | |
| } | |
| } | |