Instructions to use BroAlanTaps/Stage1-PCC-Lite-16x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BroAlanTaps/Stage1-PCC-Lite-16x with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BroAlanTaps/Stage1-PCC-Lite-16x")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BroAlanTaps/Stage1-PCC-Lite-16x") model = AutoModelForCausalLM.from_pretrained("BroAlanTaps/Stage1-PCC-Lite-16x", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download memory_converter.bin from BroAlanTaps/Stage1-PCC-Lite-16x: direct link, hf CLI and curl.
- Browser
- Download file 1.59 GB
-
https://huggingface.co/BroAlanTaps/Stage1-PCC-Lite-16x/resolve/main/memory_converter.bin
- Command line
-
hf download hf://BroAlanTaps/Stage1-PCC-Lite-16x/memory_converter.bin
-
curl -L -o memory_converter.bin https://huggingface.co/BroAlanTaps/Stage1-PCC-Lite-16x/resolve/main/memory_converter.bin
1.59 GB
- Xet hash:
- e9861fbd001238e4d3efa82df4cd16699d73f4cceed19a44d596ba05f5b0d45e
- Size of remote file:
- 1.59 GB
- SHA256:
- eeb9799e40b3787823b4cab49f64cb5fda610341873e66433a4d4817aad0397a
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