Instructions to use Alireza1044/albert-base-v2-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alireza1044/albert-base-v2-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Alireza1044/albert-base-v2-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Alireza1044/albert-base-v2-sst2") model = AutoModelForSequenceClassification.from_pretrained("Alireza1044/albert-base-v2-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Alireza1044/albert-base-v2-sst2: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/Alireza1044/albert-base-v2-sst2/resolve/main/training_args.bin
- Command line
-
hf download hf://Alireza1044/albert-base-v2-sst2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Alireza1044/albert-base-v2-sst2/resolve/main/training_args.bin
2.61 kB
- Xet hash:
- f0649b7b7e5ce0bc5b0567e58958e40003a1241beb478dc060bbadb614a93a0c
- Size of remote file:
- 2.61 kB
- SHA256:
- b388633199c3ec69f5d793e929089e5be4a7e02891c673ec492629445a5e1ba4
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