Instructions to use Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3") model = AutoModelForSequenceClassification.from_pretrained("Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3/resolve/main/training_args.bin
- Command line
-
hf download hf://Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Apoksk1/dbmdz-bertTurk-sentiment-GroundTruthV3/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 4aff044ecae8dcf2e017fa7f6cf1a982de016aeb4426e98e15d33d3f420bbe14
- Size of remote file:
- 5.18 kB
- SHA256:
- e5ebbc28050584d298c366db470dcd93cba91c408726f127dbbb5db55fd39fc6
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