nerozhao commited on
Commit
3e38ca4
·
verified ·
1 Parent(s): 3be9639

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -7,7 +7,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
7
  # Load model and tokenizer
8
  model_name = "Salesforce/xLAM-1b-fc-r"
9
 
10
- title = f"# 🚀Eval Model: {model_name}"
11
 
12
  model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype="auto", trust_remote_code=True)
13
  tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -23,8 +23,8 @@ def generate_response(query):
23
 
24
  inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
25
  outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
26
-
27
- return outputs
28
 
29
  # Gradio interface
30
  with gr.Blocks() as demo:
@@ -39,7 +39,7 @@ with gr.Blocks() as demo:
39
  submit_button = gr.Button("Generate Response")
40
 
41
  with gr.Column():
42
- output = gr.Code(label="Response :", lines=10, language="json")
43
 
44
  submit_button.click(generate_response, inputs=[query_input], outputs=output)
45
 
 
7
  # Load model and tokenizer
8
  model_name = "Salesforce/xLAM-1b-fc-r"
9
 
10
+ title = f"# 🚀 Eval Model: {model_name}"
11
 
12
  model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype="auto", trust_remote_code=True)
13
  tokenizer = AutoTokenizer.from_pretrained(model_name)
 
23
 
24
  inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
25
  outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
26
+ result = tokenizer.decode(outputs, skip_special_tokens=True)
27
+ return result
28
 
29
  # Gradio interface
30
  with gr.Blocks() as demo:
 
39
  submit_button = gr.Button("Generate Response")
40
 
41
  with gr.Column():
42
+ output = gr.Code(label="Response :", lines=20, language="json")
43
 
44
  submit_button.click(generate_response, inputs=[query_input], outputs=output)
45