Instructions to use dusersad12/SentinelLM-EvalRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/SentinelLM-EvalRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/SentinelLM-EvalRepo")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/SentinelLM-EvalRepo") model = AutoModel.from_pretrained("dusersad12/SentinelLM-EvalRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from dusersad12/SentinelLM-EvalRepo: direct link, hf CLI and curl.
- Browser
- Download file 67 Bytes
-
https://huggingface.co/dusersad12/SentinelLM-EvalRepo/resolve/main/config.json
- Command line
-
hf download hf://dusersad12/SentinelLM-EvalRepo/config.json
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curl -L -o config.json https://huggingface.co/dusersad12/SentinelLM-EvalRepo/resolve/main/config.json
67 Bytes
| { | |
| "model_type": "bert", | |
| "architectures": ["BertModel"] | |
| } | |