Create GPT

GPT

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer
+model_name = "Ransss/llama3-8B-DarkIdol-2.0-Uncensored-Q8_0-GGUF"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, load_in_8bit=True)
+
+def generate_text(prompt, max_length=100, temperature=0.7):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(
+        inputs["input_ids"],
+        max_length=max_length,
+        temperature=temperature,
+        do_sample=True,
+        top_p=0.9,
+        top_k=50,
+        num_return_sequences=1,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Create a Gradio interface
+gr.Interface(
+    fn=generate_text,
+    inputs=[
+        gr.inputs.Textbox(label="Input Text"),
+        gr.inputs.Slider(label="Max Length", minimum=1, maximum=500, value=100, step=1),
+        gr.inputs.Slider(label="Temperature", minimum=0.1, maximum=1.0, value=0.7, step=0.1),
+    ],
+    outputs=gr.outputs.Textbox(label="Generated Text"),
+    title="LLAMA 3 8B Model",
+    description="Generate text using the LLAMA 3 8B model.",
+).launch()