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b0a826f 0710173 b0a826f 0710173 b0a826f 0710173 134ca8e 0710173 134ca8e b0a826f 0710173 b0a826f 0710173 b0a826f 134ca8e 0710173 134ca8e 0710173 b0a826f 0710173 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | import gradio as gr
from huggingface_hub import hf_hub_download
from llama_cpp import Llama
# 📥 Model Download
model_path = hf_hub_download(
repo_id="RockSky1/Infinity_1.0",
filename="Infinity_1.0.gguf"
)
print("Loading model...")
llm = Llama(
model_path=model_path,
n_ctx=512,
n_threads=2,
n_batch=128
)
print("Model loaded ✅")
def chat_function(message, history):
try:
output = llm.create_chat_completion(
messages=[
{
"role": "system",
"content": "You are Infinity AI 🔥 created by Shivam Kumar (RockSky1) from Bihar, India."
},
*[
{"role": "user", "content": h[0]} if i % 2 == 0
else {"role": "assistant", "content": h[1]}
for i, h in enumerate(history)
],
{"role": "user", "content": message}
],
max_tokens=128,
temperature=0.7
)
reply = output["choices"][0]["message"]["content"]
except Exception as e:
reply = f"Error: {str(e)}"
return reply
with gr.Blocks() as demo:
gr.Markdown("# ♾️ Infinity-LLM v1.0 🚀")
gr.ChatInterface(
fn=chat_function,
examples=[
"Who is Shivam Kumar?",
"Tell me about Infinity-LLM.",
"Write a simple Python script."
]
)
demo.launch() |