Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Valencio/LLM_course_MLM_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Valencio/LLM_course_MLM_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Valencio/LLM_course_MLM_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Valencio/LLM_course_MLM_model") model = AutoModelForSequenceClassification.from_pretrained("Valencio/LLM_course_MLM_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd5f44ea559e1f936ed37482badba20e73c3839d385e62450ce4c4e6bb4c6f33
- Size of remote file:
- 5.2 kB
- SHA256:
- d75b9357edb236bcc253d92ceaae9c666a6c88cd4ae072a95f96c2415251686c
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