Feature Extraction
Transformers
English
qwen3
text-generation-inference
unsloth
text-embeddings-inference
Instructions to use akarshaurora/qwen3-14B-instruct-medical-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akarshaurora/qwen3-14B-instruct-medical-coder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="akarshaurora/qwen3-14B-instruct-medical-coder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("akarshaurora/qwen3-14B-instruct-medical-coder") model = AutoModel.from_pretrained("akarshaurora/qwen3-14B-instruct-medical-coder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded finetuned model
- Developed by: akarshaurora
- License: apache-2.0
- Finetuned from model : unsloth/Qwen3-14B-unsloth-bnb-4bit
This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Model tree for akarshaurora/qwen3-14B-instruct-medical-coder
Base model
Qwen/Qwen3-14B-Base Finetuned
Qwen/Qwen3-14B Quantized
unsloth/Qwen3-14B-unsloth-bnb-4bit