Instructions to use lichangh20/s1k_format_filtered with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lichangh20/s1k_format_filtered with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lichangh20/s1k_format_filtered")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lichangh20/s1k_format_filtered") model = AutoModel.from_pretrained("lichangh20/s1k_format_filtered", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from lichangh20/s1k_format_filtered: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/lichangh20/s1k_format_filtered/resolve/main/tokenizer.json
- Command line
-
hf download hf://lichangh20/s1k_format_filtered/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/lichangh20/s1k_format_filtered/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 3994cc3f50f60ab829c0eb619c37cb98f06dca4f42ee44f0c09eafddc8def616
- Size of remote file:
- 11.4 MB
- SHA256:
- 9ffb4bd5c40b82c8e9ee9be5eb1632ad555eb42250ccc4eece6325a37e78ba1a
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