Text Classification
Transformers
Safetensors
English
qwen2
text-generation
code
qwen
openhusky-coder
text-embeddings-inference
Instructions to use CodeDevX/openhusky-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeDevX/openhusky-coder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeDevX/openhusky-coder")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CodeDevX/openhusky-coder") model = AutoModelForCausalLM.from_pretrained("CodeDevX/openhusky-coder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbb70034f388dc31082a479e39d9325d2b5058b0659935e4bf5a55ae002c9bae
- Size of remote file:
- 932 MB
- SHA256:
- 338458aab7b67425645d209205ef9e2f08802958643f6af471751cc2f79fe220
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