Text Classification
Transformers
TensorBoard
Safetensors
bert
glue
rte
max_length_128
dropout_0.4
Generated from Trainer
text-embeddings-inference
Instructions to use ipeksnmz/bert-base-uncased-finetuned-rte-run_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ipeksnmz/bert-base-uncased-finetuned-rte-run_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ipeksnmz/bert-base-uncased-finetuned-rte-run_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ipeksnmz/bert-base-uncased-finetuned-rte-run_3") model = AutoModelForSequenceClassification.from_pretrained("ipeksnmz/bert-base-uncased-finetuned-rte-run_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download run-7/checkpoint-195/training_args.bin from ipeksnmz/bert-base-uncased-finetuned-rte-run_3: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/ipeksnmz/bert-base-uncased-finetuned-rte-run_3/resolve/main/run-7/checkpoint-195/training_args.bin
- Command line
-
hf download hf://ipeksnmz/bert-base-uncased-finetuned-rte-run_3/run-7/checkpoint-195/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ipeksnmz/bert-base-uncased-finetuned-rte-run_3/resolve/main/run-7/checkpoint-195/training_args.bin
5.43 kB
- Xet hash:
- abf4525726a46606ef37b9eab627d4561e2e01e2d08544ff3100fe26548dc78d
- Size of remote file:
- 5.43 kB
- SHA256:
- c3c0d10f61e17d71a323468259be20cf778ab0e5cb49a81ab869fa68120b076e
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