Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use halu1003/LLMClassWork1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halu1003/LLMClassWork1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="halu1003/LLMClassWork1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("halu1003/LLMClassWork1") model = AutoModelForSequenceClassification.from_pretrained("halu1003/LLMClassWork1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb61c77e30838e4dbf535595e98f822a575fdd0c84f7f38da8888d4511f0ca3d
- Size of remote file:
- 536 MB
- SHA256:
- 033a502df8b6a0d1b930b66d0fadc5d72ed70d78e9103c8fa2efc4d5bc99f263
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