Instructions to use hyper-accel/tiny-random-internlm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyper-accel/tiny-random-internlm2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hyper-accel/tiny-random-internlm2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hyper-accel/tiny-random-internlm2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e05bae4729ed19ce27bd51e87e121e23ab9d0b504cb022f3665750c62e84c1cd
- Size of remote file:
- 867 MB
- SHA256:
- 120e119166360c7c8237587c06e60439a5efc741a5e2f44ea16f0ae561c1ec13
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