Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use aabidk/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aabidk/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aabidk/test-trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aabidk/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("aabidk/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from aabidk/test-trainer: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/aabidk/test-trainer/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://aabidk/test-trainer/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aabidk/test-trainer/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- bd7c61a16e395fba33fba721012f3e5b59890c9f2e209502988fe437464fe67c
- Size of remote file:
- 438 MB
- SHA256:
- cec11ff00eec96238c1d2982bb8c696a1812cf1054ce59ee2271c09de925fc9d
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