Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Asmatullah-AI-Engineer/ai_vet_agent_transformer_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Asmatullah-AI-Engineer/ai_vet_agent_transformer_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Asmatullah-AI-Engineer/ai_vet_agent_transformer_model", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Asmatullah-AI-Engineer/ai_vet_agent_transformer_model") model = AutoModelForSequenceClassification.from_pretrained("Asmatullah-AI-Engineer/ai_vet_agent_transformer_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 131c061997d633dbd0d253bb055a78e31e6f382f78a12ed2e0613eed31317910
- Size of remote file:
- 5.2 kB
- SHA256:
- 30984562547a186e8be82827d2431103782b2c9c5b607869a9a0954ddf2c1448
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.