Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use CCChenRyan/LLM_T1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CCChenRyan/LLM_T1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CCChenRyan/LLM_T1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CCChenRyan/LLM_T1") model = AutoModelForSequenceClassification.from_pretrained("CCChenRyan/LLM_T1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b2f25529e2e4d13df5a99a9667e953522b43222a1053b525808a8516e37f5e8
- Size of remote file:
- 4.79 kB
- SHA256:
- ca90f88161a3b114eb96ba6a890c567afdbf02e037dfbb031a9323ba1018eb1b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.