Instructions to use dusersad12/FineTunedBest-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/FineTunedBest-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dusersad12/FineTunedBest-TestRepo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dusersad12/FineTunedBest-TestRepo") model = AutoModelForSequenceClassification.from_pretrained("dusersad12/FineTunedBest-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload FineTunedBest model (run_gamma, best by eval_accuracy) with filled-in benchmark scores
8ef5ecf verified Download pytorch_model.bin from dusersad12/FineTunedBest-TestRepo: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
-
https://huggingface.co/dusersad12/FineTunedBest-TestRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/FineTunedBest-TestRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/FineTunedBest-TestRepo/resolve/main/pytorch_model.bin
28 Bytes
- Xet hash:
- 7a0cd9d79c11bf997ddc726e07300a45fc5f7cdef33aaf4763b9ea21b07e2f01
- Size of remote file:
- 28 Bytes
- SHA256:
- 63fdef5f6fdfddc1e16513b3faab0bf7f823c1fb0d762c03a7e6f2fcfe88be63
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