Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use himanshu007/query_check_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use himanshu007/query_check_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="himanshu007/query_check_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("himanshu007/query_check_model") model = AutoModelForSequenceClassification.from_pretrained("himanshu007/query_check_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65ab55f360a3b608f26b2ff08ae61d0ccf14cab4968444d13eb342496c87466d
- Size of remote file:
- 4.92 kB
- SHA256:
- 6f0568fd53c23801991ce4ca6291c26522c44233fc42e5da3ffa4f8f8c044d24
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.