Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use RayenLLM/bert-practice-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RayenLLM/bert-practice-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RayenLLM/bert-practice-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RayenLLM/bert-practice-classifier") model = AutoModelForSequenceClassification.from_pretrained("RayenLLM/bert-practice-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from RayenLLM/bert-practice-classifier: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/RayenLLM/bert-practice-classifier/resolve/main/model.safetensors
- Command line
-
hf download hf://RayenLLM/bert-practice-classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/RayenLLM/bert-practice-classifier/resolve/main/model.safetensors
268 MB
- Xet hash:
- 84d06af9d8894a5136dc2df29cdc310dc64aba164bce94b3819cfc092a59e3a1
- Size of remote file:
- 268 MB
- SHA256:
- 6c24afbd14d800508ffeba0e879058592bc80be0249c49f78f7029ba5efb14ed
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