Instructions to use EricPeter/ktrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EricPeter/ktrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EricPeter/ktrain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EricPeter/ktrain") model = AutoModelForSequenceClassification.from_pretrained("EricPeter/ktrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from EricPeter/ktrain: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/EricPeter/ktrain/resolve/main/tf_model.h5
- Command line
-
hf download hf://EricPeter/ktrain/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/EricPeter/ktrain/resolve/main/tf_model.h5
1.11 GB
- Xet hash:
- d323591415271ac0f997dcdeb8fc02be555e3bc02bf936cc154bf03bd23c5f4d
- Size of remote file:
- 1.11 GB
- SHA256:
- 3879162c8de773748c29d7612ce227898d6131565125d2c1751caaec13efcfe9
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