Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use cerrano/myFirstModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cerrano/myFirstModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cerrano/myFirstModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cerrano/myFirstModel") model = AutoModelForSequenceClassification.from_pretrained("cerrano/myFirstModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from cerrano/myFirstModel: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/cerrano/myFirstModel/resolve/main/model.safetensors
- Command line
-
hf download hf://cerrano/myFirstModel/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/cerrano/myFirstModel/resolve/main/model.safetensors
268 MB
- Xet hash:
- 83ac382eebd6e0e473041f8b6bcc6afa875c3941b32c0e871426eb59d8abab63
- Size of remote file:
- 268 MB
- SHA256:
- 8e0bbbc406b04448fc06b54b6579cad15112a326544826c4134c3dacd98a4541
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.