Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AndreiUrsu/finetuning-sentiment-model-3000-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndreiUrsu/finetuning-sentiment-model-3000-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndreiUrsu/finetuning-sentiment-model-3000-samples")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndreiUrsu/finetuning-sentiment-model-3000-samples") model = AutoModelForSequenceClassification.from_pretrained("AndreiUrsu/finetuning-sentiment-model-3000-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AndreiUrsu/finetuning-sentiment-model-3000-samples: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/AndreiUrsu/finetuning-sentiment-model-3000-samples/resolve/main/training_args.bin
- Command line
-
hf download hf://AndreiUrsu/finetuning-sentiment-model-3000-samples/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AndreiUrsu/finetuning-sentiment-model-3000-samples/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 53e849a932721c9d5f462e57bc026df2d6ec342c851082a7a685a6261a989f75
- Size of remote file:
- 4.98 kB
- SHA256:
- a6ae2edf46485e87cc4e67af0b32258ae26be96ff150bcebbe116bfaf6ddbff2
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