cycloarcane_-_QWARG-test-gguf

Quantization made by Richard Erkhov.

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QWARG-test - GGUF

• Model creator: https://huggingface.co/cycloarcane/
• Original model: https://huggingface.co/cycloarcane/QWARG-test/

Original model description:

tags:

• autotrain
• text-generation-inference
• text-generation library_name: transformers base_model: Qwen/Qwen2.5-1.5B-Instruct widget:
  • messages:
    • role: user content: What is your favorite condiment? license: other

---

Model Trained Using AutoTrain

This model was trained using AutoTrain. For more information, please visit AutoTrain. I was testing how easy it is to get a consistent output that included special characters using just 3 epochs with 10000 data entries. The model outputs the string "|--MY NAME IS QWARG--|" after most reponses.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "PATH_TO_THIS_REPO"

tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
    model_path,
    device_map="auto",
    torch_dtype='auto'
).eval()

# Prompt content: "hi"
messages = [
    {"role": "user", "content": "hi"}
]

input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)

# Model response: "Hello! How can I assist you today?"
print(response)