初始化项目，由ModelHub XC社区提供模型

Model: Vaisu23/ner-qwen_model
Source: Original Platform

README.md

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+---
+base_model: unsloth/qwen2.5-0.5b-unsloth-bnb-4bit
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen2
+license: apache-2.0
+language:
+- en
+---
+
+# Uploaded finetuned  model
+
+- **Developed by:** Vaisu23
+- **License:** apache-2.0
+- **Finetuned from model :** unsloth/qwen2.5-0.5b-unsloth-bnb-4bit
+
+This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+
+
+
+# Financial NER Qwen
+
+This model is fine-tuned for high-accuracy Named Entity Recognition (NER), outputting structured JSON.
+
+## How to use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "Vaisu23/ner-qwen_model" # Update this to your repo ID
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, 
+    torch_dtype=torch.float16, 
+    device_map="auto"
+)
+
+# 1. Set the ChatML template
+tokenizer.chat_template = "{{% for message in messages %}}{{{{'<|im_start|>' + message['role'] + '\\n' + message['content'] + '<|im_end|>' + '\\n'}}}}% endfor %}{{% if add_generation_prompt %}}{{{{ '<|im_start|>assistant\\n' }}}}{% endif %}}"
+
+# 2. Prepare the input
+messages = [
+    {{"role": "system", "content": "Extract all entities from the text in a structured JSON format."}},
+    {{"role": "user", "content": "Yesterday, Vaisakh P K spent 1250.50 USD at Google."}}
+]
+
+inputs = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt",
+    return_dict=True
+).to("cuda")
+
+# 3. Generate and clean the output
+with torch.no_grad():
+    outputs = model.generate(**inputs, max_new_tokens=128, temperature=0.1)
+
+# Skip the prompt tokens to show ONLY the JSON
+prediction_ids = outputs[0][len(inputs['input_ids'][0]):]
+prediction = tokenizer.decode(prediction_ids, skip_special_tokens=True)
+
+print(prediction)
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)