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 training_args.bin from aabidk/test-trainer: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/aabidk/test-trainer/resolve/main/training_args.bin
- Command line
-
hf download hf://aabidk/test-trainer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aabidk/test-trainer/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- 36e4d46b81b358e7a17fb3272bd2ba2bdbca5a13ae6c90e1f3a79a852e0cd939
- Size of remote file:
- 3.9 kB
- SHA256:
- e32b7aa7498534e69af75d8e58c578ea299464d7f5901f5370bf8aa0a9dab381
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