Token Classification
Transformers
TensorBoard
Safetensors
gpt2
Generated from Trainer
text-generation-inference
Instructions to use kthammana/MLMA-Lab8-FinetunedBioGPT-Custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kthammana/MLMA-Lab8-FinetunedBioGPT-Custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kthammana/MLMA-Lab8-FinetunedBioGPT-Custom")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kthammana/MLMA-Lab8-FinetunedBioGPT-Custom") model = AutoModelForTokenClassification.from_pretrained("kthammana/MLMA-Lab8-FinetunedBioGPT-Custom") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fcb89fc76055f436c0aec4df3b101b4b5b2792d06abf57f00c1340cb517ba25
- Size of remote file:
- 1.39 GB
- SHA256:
- b5e11007d36863177efdbc2424e4690e09fe4454fe1e5bd57b980d7bc7c7f275
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