Instructions to use moussaKam/tiny_bert-base_bert-score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moussaKam/tiny_bert-base_bert-score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moussaKam/tiny_bert-base_bert-score")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moussaKam/tiny_bert-base_bert-score") model = AutoModelForSequenceClassification.from_pretrained("moussaKam/tiny_bert-base_bert-score", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from moussaKam/tiny_bert-base_bert-score: direct link, hf CLI and curl.
- Browser
- Download file 467 Bytes
-
https://huggingface.co/moussaKam/tiny_bert-base_bert-score/resolve/main/train_results.json
- Command line
-
hf download hf://moussaKam/tiny_bert-base_bert-score/train_results.json
-
curl -L -o train_results.json https://huggingface.co/moussaKam/tiny_bert-base_bert-score/resolve/main/train_results.json
467 Bytes
| { | |
| "epoch": 3.0, | |
| "init_mem_cpu_alloc_delta": 2160803840, | |
| "init_mem_cpu_peaked_delta": 12996608, | |
| "init_mem_gpu_alloc_delta": 17548800, | |
| "init_mem_gpu_peaked_delta": 0, | |
| "train_mem_cpu_alloc_delta": 14491648000, | |
| "train_mem_cpu_peaked_delta": 174706688, | |
| "train_mem_gpu_alloc_delta": 53029376, | |
| "train_mem_gpu_peaked_delta": 669877760, | |
| "train_runtime": 37325.4581, | |
| "train_samples": 4500000, | |
| "train_samples_per_second": 11.303 | |
| } |