Text Classification
Transformers
Safetensors
English
llama
text-generation
intent-classification
awq
Eval Results (legacy)
text-embeddings-inference
4-bit precision
Instructions to use emasoga3/llama3-intent-awq-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emasoga3/llama3-intent-awq-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emasoga3/llama3-intent-awq-4bit")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("emasoga3/llama3-intent-awq-4bit") model = AutoModelForMultimodalLM.from_pretrained("emasoga3/llama3-intent-awq-4bit") - Notebooks
- Google Colab
- Kaggle
Upload model-00001-of-00002.safetensors with huggingface_hub
Browse files
model-00001-of-00002.safetensors
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