Token Classification
Transformers
Safetensors
llama
Generated from Trainer
text-generation-inference
Instructions to use mtzig/tinyllama_run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtzig/tinyllama_run with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mtzig/tinyllama_run")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mtzig/tinyllama_run") model = AutoModelForTokenClassification.from_pretrained("mtzig/tinyllama_run") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75ae7f1045c829336451b90da73aa44a8d0e9dc3345b85278a391fe3511af1e1
- Size of remote file:
- 535 MB
- SHA256:
- 9d76c18094db0a6079443470fbb0c2745f75acb29740bcfe3e53b29eb2c93213
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