Feature Extraction
Transformers
Safetensors
qwen3
text-generation
embeddings
legal-retrieval
procurement
lora-merged
text-embeddings-inference
Instructions to use LorMolf/Qwen-Embedding-ProcCode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LorMolf/Qwen-Embedding-ProcCode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LorMolf/Qwen-Embedding-ProcCode")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LorMolf/Qwen-Embedding-ProcCode") model = AutoModelForCausalLM.from_pretrained("LorMolf/Qwen-Embedding-ProcCode") - Notebooks
- Google Colab
- Kaggle
File size: 117 Bytes
968e75c | 1 2 3 4 5 6 7 | {
"bos_token_id": 151643,
"eos_token_id": 151643,
"max_new_tokens": 2048,
"transformers_version": "5.10.2"
}
|