Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned") model = AutoModelForSequenceClassification.from_pretrained("Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned/resolve/main/model.safetensors
- Command line
-
hf download hf://Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Carick/distilbert-base-uncased-wordnet_dataset_three-fine-tuned/resolve/main/model.safetensors
268 MB
- Xet hash:
- efc44071e42749492b1c726585f7b66390874d5c8c571b7197393d53a4092b2e
- Size of remote file:
- 268 MB
- SHA256:
- 538a8cd07c5921b244c193197ff6d52316a927b3eb343858d9fbfb70c8dd13e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.