Instructions to use Hikam22/Review with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hikam22/Review with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Hikam22/Review")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Hikam22/Review") model = AutoModelForMaskedLM.from_pretrained("Hikam22/Review", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Hikam22/Review: direct link, hf CLI and curl.
- Browser
- Download file 736 kB
-
https://huggingface.co/Hikam22/Review/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://Hikam22/Review@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Hikam22/Review/resolve/refs%2Fpr%2F1/tokenizer.json
736 kB
File too large to display, you can check the raw version instead.