Text Classification
Transformers
TensorBoard
Safetensors
llama
Generated from Trainer
text-embeddings-inference
Instructions to use rd211/SmolLM2-1.7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rd211/SmolLM2-1.7B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rd211/SmolLM2-1.7B-Instruct")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rd211/SmolLM2-1.7B-Instruct") model = AutoModelForSequenceClassification.from_pretrained("rd211/SmolLM2-1.7B-Instruct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2402e6142d91da349bb62112e7028da6e3f30c41cb5a39896d092a1b1463d8c6
- Size of remote file:
- 5.37 kB
- SHA256:
- 5ad1637febd61054b99e469a057c52c0158b2cb0b731f1fcfeeab95763bcc00e
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