Text Classification
Transformers
PyTorch
TensorBoard
data2vec-text
Generated from Trainer
Eval Results (legacy)
Instructions to use mrm8488/data2vec-text-base-finetuned-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/data2vec-text-base-finetuned-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/data2vec-text-base-finetuned-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/data2vec-text-base-finetuned-mnli") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/data2vec-text-base-finetuned-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mrm8488/data2vec-text-base-finetuned-mnli: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/mrm8488/data2vec-text-base-finetuned-mnli/resolve/main/training_args.bin
- Command line
-
hf download hf://mrm8488/data2vec-text-base-finetuned-mnli/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mrm8488/data2vec-text-base-finetuned-mnli/resolve/main/training_args.bin
3.12 kB
- Xet hash:
- dd5a09239d3f4ae9b987af35522ba56bf59e328d25dc5b7bd780e26d75e3b9fe
- Size of remote file:
- 3.12 kB
- SHA256:
- 48e8ea24e77ede7fd6f7a54627a2bba1917acde1d1ccbff52c68145a75fd3097
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