Text Classification
Transformers
PyTorch
Safetensors
Portuguese
llama
textual-entailment
text-embeddings-inference
Instructions to use nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI") model = AutoModelForSequenceClassification.from_pretrained("nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI/resolve/main/training_args.bin
- Command line
-
hf download hf://nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nicholasKluge/TeenyTinyLlama-160m-FaQuAD-NLI/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- a14f8c536da5be54b99d4e0e04d1dade1d9eab8ed1dd679689acf6f59c40d84b
- Size of remote file:
- 4.66 kB
- SHA256:
- 81b766b7f7be78bc4fe022ea88ce59265bfabc4c739c135d490a9c8e4d54701b
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