Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use rach405/test_trainer3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rach405/test_trainer3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rach405/test_trainer3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rach405/test_trainer3") model = AutoModelForSequenceClassification.from_pretrained("rach405/test_trainer3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rach405/test_trainer3: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/rach405/test_trainer3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rach405/test_trainer3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rach405/test_trainer3/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 24316dd850b1c26b0edf0ebfba67698b0c8cbd5f307a78286213588b70a7bde9
- Size of remote file:
- 433 MB
- SHA256:
- 1f65665fc26851e23c35999127e637cbe7e050b9826f09ca1595d054de4592e9
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