Instructions to use context-sbf/charm-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use context-sbf/charm-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("context-sbf/charm-large") model = AutoModelForSeq2SeqLM.from_pretrained("context-sbf/charm-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download index.html from context-sbf/charm-large: direct link, hf CLI and curl.
- Browser
- Download file 791 Bytes
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https://huggingface.co/context-sbf/charm-large/resolve/main/index.html
- Command line
-
hf download hf://context-sbf/charm-large/index.html
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curl -L -o index.html https://huggingface.co/context-sbf/charm-large/resolve/main/index.html
791 Bytes
| <html> | |
| <head> | |
| <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> | |
| <title>Directory listing for /.log/explain-model-large/</title> | |
| </head> | |
| <body> | |
| <h1>Directory listing for /.log/explain-model-large/</h1> | |
| <hr> | |
| <ul> | |
| <li><a href="answer.csv">answer.csv</a></li> | |
| <li><a href="config.json">config.json</a></li> | |
| <li><a href="pytorch_model.bin">pytorch_model.bin</a></li> | |
| <li><a href="results.csv">results.csv</a></li> | |
| <li><a href="special_tokens_map.json">special_tokens_map.json</a></li> | |
| <li><a href="spiece.model">spiece.model</a></li> | |
| <li><a href="tokenizer_config.json">tokenizer_config.json</a></li> | |
| <li><a href="training_args.bin">training_args.bin</a></li> | |
| </ul> | |
| <hr> | |
| </body> | |
| </html> | |