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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CodeDevX/openhusky-coder") model = AutoModelForCausalLM.from_pretrained("CodeDevX/openhusky-coder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CodeDevX/openhusky-coder: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/CodeDevX/openhusky-coder/resolve/main/tokenizer.json
- Command line
-
hf download hf://CodeDevX/openhusky-coder/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CodeDevX/openhusky-coder/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- d3f835122bddb470f53048ff36f1a5116791b8f3a003f9d17b3b03b0b81cc5fe
- Size of remote file:
- 11.4 MB
- SHA256:
- 3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
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