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-4501/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-4501/optimizer.pt
- Command line
-
hf download hf://xshubhamx/tiny-mistral/training_checkpoints/checkpoint-4501/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/xshubhamx/tiny-mistral/resolve/main/training_checkpoints/checkpoint-4501/optimizer.pt
1.58 GB
- Xet hash:
- b4e1dac9051a453159ad97be1eedbbad2642462fd5932db0a85cf97d13dc2342
- Size of remote file:
- 1.58 GB
- SHA256:
- 29444c59671e9b6eba7114498599b6582608a8643ee52403ccbae1ffb2b1ceb0
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