Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use liambyrne/distilbert-stackoverflow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liambyrne/distilbert-stackoverflow with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="liambyrne/distilbert-stackoverflow")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("liambyrne/distilbert-stackoverflow") model = AutoModelForSequenceClassification.from_pretrained("liambyrne/distilbert-stackoverflow", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from liambyrne/distilbert-stackoverflow: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/liambyrne/distilbert-stackoverflow/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://liambyrne/distilbert-stackoverflow/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/liambyrne/distilbert-stackoverflow/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- f6735328bc5438b8aba1e20a713f68b336968a819c6ec3a8270753d443b19da4
- Size of remote file:
- 268 MB
- SHA256:
- 8cc463e7130c6bfdc0efaaba5394c094e9e3316436009e1baaa4146748714ae2
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