Instructions to use hf-internal-testing/tiny-random-GPTNeoForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-GPTNeoForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 132 Bytes
bf2090d | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:5bc8a8e89c10ba2ba2be77b06fd2894653d75b0575f2fef7c5266e58d2a0cbf6
size 1467508
|