Text Classification
Transformers
TensorBoard
Safetensors
mistral
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/tiny-mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/tiny-mistral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/tiny-mistral")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/tiny-mistral") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/tiny-mistral", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8d40cfd685d97dbb6516aa13c68448aeb4c371f5c10a40cc13c12c71396e360
- Size of remote file:
- 1.58 GB
- SHA256:
- 4a430152a2cd1918af72131a09877fef7ce018c3ce743214381d492021e6a341
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