Instructions to use dusersad12/OrionLM-Checkpoint-Release with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/OrionLM-Checkpoint-Release with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/OrionLM-Checkpoint-Release")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/OrionLM-Checkpoint-Release") model = AutoModel.from_pretrained("dusersad12/OrionLM-Checkpoint-Release", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/OrionLM-Checkpoint-Release: direct link, hf CLI and curl.
- Browser
- Download file 27 Bytes
-
https://huggingface.co/dusersad12/OrionLM-Checkpoint-Release/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/OrionLM-Checkpoint-Release/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/OrionLM-Checkpoint-Release/resolve/main/pytorch_model.bin
27 Bytes
- Xet hash:
- d1b60fa2e5dc5943072b2a27f679db93c85d6fb7e273986b5720f130742f410d
- Size of remote file:
- 27 Bytes
- SHA256:
- d2416b138e93d6d629105fa29c1f55fcb0360f13ce84dd259ec7bcdc113b7bbb
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