Instructions to use LyH88/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LyH88/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LyH88/finetuning-sentiment-model-3000-samples")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LyH88/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("LyH88/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
finetuning-sentiment-model-3000-samples / runs /Mar23_21-34-04_MacBook-Pro /events.out.tfevents.1711244050.MacBook-Pro.90430.0
- Xet hash:
- b37bab0e35a74aa9e5c4fff9d6c1a89a7e0048b4f713ce43847f76848f5331ce
- Size of remote file:
- 4.51 kB
- SHA256:
- d4897e3b84ae372683813cab64b0cd79b1bd533f407da55abf1b277234470823
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