Instructions to use KPROCKS/Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KPROCKS/Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KPROCKS/Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KPROCKS/Model") model = AutoModelForSequenceClassification.from_pretrained("KPROCKS/Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from KPROCKS/Model: direct link, hf CLI and curl.
- Browser
- Download file 950 MB
-
https://huggingface.co/KPROCKS/Model/resolve/main/model.safetensors
- Command line
-
hf download hf://KPROCKS/Model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/KPROCKS/Model/resolve/main/model.safetensors
950 MB
- Xet hash:
- fc6c2bd13c0f5d783934806e3eb17f5f7783d4b32c5e3bb0f25b5e4b09f5d3fd
- Size of remote file:
- 950 MB
- SHA256:
- 6768b3350c5b1c63261042dc6182b7d00b9d685328aa5be1f3abe4140d471858
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