Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Hartunka/tiny_bert_rand_20_v1_qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/tiny_bert_rand_20_v1_qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hartunka/tiny_bert_rand_20_v1_qqp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hartunka/tiny_bert_rand_20_v1_qqp") model = AutoModelForSequenceClassification.from_pretrained("Hartunka/tiny_bert_rand_20_v1_qqp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Hartunka/tiny_bert_rand_20_v1_qqp: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Hartunka/tiny_bert_rand_20_v1_qqp/resolve/main/training_args.bin
- Command line
-
hf download hf://Hartunka/tiny_bert_rand_20_v1_qqp/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Hartunka/tiny_bert_rand_20_v1_qqp/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- ca68d467ebc2ac06d6573de8a99889756892e437f2e8c2deb692e763f5efb3be
- Size of remote file:
- 5.37 kB
- SHA256:
- cde9569ebd21e525e749e6b17a1ef4d0b5d3ca09ea4aaa26c202db7b009984de
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