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")# pip install -U transformers accelerate # 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
Download training_checkpoints/checkpoint-9002/optimizer.pt from xshubhamx/tiny-mistral: direct link, hf CLI and curl.
- Browser
- Download file 1.58 GB
-
https://huggingface.co/xshubhamx/tiny-mistral/resolve/main/training_checkpoints/checkpoint-9002/optimizer.pt
- Command line
-
hf download hf://xshubhamx/tiny-mistral/training_checkpoints/checkpoint-9002/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/xshubhamx/tiny-mistral/resolve/main/training_checkpoints/checkpoint-9002/optimizer.pt
1.58 GB
- Xet hash:
- d41e2749406432620e85d3a005ffda6bcce66b5707d2abf428b5678983553105
- Size of remote file:
- 1.58 GB
- SHA256:
- 29b52e6121d5d93266a9cb59ca633bc0d14b4ef673e3ceb6e40d3a04f89585b9
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