Question Answering
Transformers
Safetensors
mistral
text-generation
Merge
mergekit
lazymergekit
huggingface/CodeBERTa-language-id
Sharathhebbar24/code_gpt2
text-generation-inference
Instructions to use nagayama0706/coding_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nagayama0706/coding_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nagayama0706/coding_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("nagayama0706/coding_model") model = AutoModelForMultimodalLM.from_pretrained("nagayama0706/coding_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a33f42223487534e077c599260b18b29d664bc98e89ddc5404ce0f49f3ba5c9b
- Size of remote file:
- 1.95 GB
- SHA256:
- 2e525c7fcd79e61d0590383492db510735ef3355188c316b59087e042aef2c6e
路
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