Instructions to use safafa34235/MyAwesomeModel-TestRepository with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use safafa34235/MyAwesomeModel-TestRepository with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="safafa34235/MyAwesomeModel-TestRepository")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("safafa34235/MyAwesomeModel-TestRepository") model = AutoModel.from_pretrained("safafa34235/MyAwesomeModel-TestRepository", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 735 Bytes
d46c8a8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"selection_criterion": "highest eval_accuracy among workspace checkpoints",
"eval_accuracy_benchmark": "text_classification",
"selected_checkpoint": "checkpoints/step_1000",
"eval_accuracy": 0.828,
"score_decimal_places": 3,
"benchmark_scores": {
"math_reasoning": 0.55,
"logical_reasoning": 0.819,
"common_sense": 0.736,
"reading_comprehension": 0.7,
"question_answering": 0.607,
"text_classification": 0.828,
"sentiment_analysis": 0.792,
"code_generation": 0.65,
"creative_writing": 0.61,
"dialogue_generation": 0.644,
"summarization": 0.767,
"translation": 0.804,
"knowledge_retrieval": 0.676,
"instruction_following": 0.758,
"safety_evaluation": 0.739
}
} |