Instructions to use arcadia-impact/scimt-dispatch-final-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arcadia-impact/scimt-dispatch-final-v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("arcadia-impact/scimt-dispatch-final-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download control/midtrain/training_examples.jsonl from arcadia-impact/scimt-dispatch-final-v1: direct link, hf CLI and curl.
- Browser
- Download file 30.7 MB
-
https://huggingface.co/arcadia-impact/scimt-dispatch-final-v1/resolve/main/control/midtrain/training_examples.jsonl
- Command line
-
hf download hf://arcadia-impact/scimt-dispatch-final-v1/control/midtrain/training_examples.jsonl
-
curl -L -o training_examples.jsonl https://huggingface.co/arcadia-impact/scimt-dispatch-final-v1/resolve/main/control/midtrain/training_examples.jsonl
30.7 MB
- Xet hash:
- 9043c9ce3df2dcf77590968844c0a01df84fc489cf0274e48b339fc18712214d
- Size of remote file:
- 30.7 MB
- SHA256:
- d1b1d06926d68a93c57ef7bc2b63ed4a20abb9c299fa1eb2e1b2136d3eac81cc
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