f

app.py

@@ -1,14 +1,9 @@
 import gradio as gr
-<<<<<<< HEAD
 from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, GenerationConfig
-=======
-from transformers import AutoModelForCausalLM, AutoTokenizer
->>>>>>> 900e0aa32e9a9ed4a7304c86d90ad89586c21aa3
 import torch
 import threading
 from queue import Queue
 
-<<<<<<< HEAD
 # Custom Streamer Class
 class MyStreamer(TextStreamer):
     def __init__(self, tokenizer, skip_prompt=True, **decode_kwargs):
@@ -28,11 +23,6 @@ class MyStreamer(TextStreamer):
             raise ValueError("put() only supports a single sequence of tokens at a time.")
         elif len(value.shape) > 1:
             value = value[0]
-=======
-model_name = "genaforvena/huivam_finnegan_llama3.2-1b"
-model = AutoModelForCausalLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
->>>>>>> 900e0aa32e9a9ed4a7304c86d90ad89586c21aa3
 
         if self.skip_prompt and self.next_tokens_are_prompt:
             self.next_tokens_are_prompt = False

requirements.txt

@@ -1,5 +1,4 @@
 huggingface_hub==0.25.2
 gradio
 transformers
-torch
-unsloth
+torch