Instructions to use sampathlonka/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sampathlonka/tmp_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sampathlonka/tmp_trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sampathlonka/tmp_trainer") model = AutoModelForMaskedLM.from_pretrained("sampathlonka/tmp_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sampathlonka/tmp_trainer: direct link, hf CLI and curl.
- Browser
- Download file 2.76 MB
-
https://huggingface.co/sampathlonka/tmp_trainer/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
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hf download hf://sampathlonka/tmp_trainer@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/sampathlonka/tmp_trainer/resolve/refs%2Fpr%2F1/tokenizer.json
2.76 MB
File too large to display, you can check the raw version instead.