Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Randomui/gene_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Randomui/gene_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Randomui/gene_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Randomui/gene_finetuned") model = AutoModelForTokenClassification.from_pretrained("Randomui/gene_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47d8e06c89d9f4117578441855123f81d159ff09b330e0b3f3223ea3e45b6bc8
- Size of remote file:
- 436 MB
- SHA256:
- 977e307e8e9f6b119e1ce94d574157e39ae6a4b58a98e61fa64cdb801a2d7655
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