Spaces:
Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
@@ -17,7 +17,7 @@ demo.launch()
|
|
17 |
#!pip install accelerate
|
18 |
#!pip install -i
|
19 |
|
20 |
-
|
21 |
|
22 |
import gradio as gr
|
23 |
import torch
|
@@ -29,17 +29,17 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
|
|
29 |
peft_model_id = "charansr/llama2-7b-chat-hf-therapist"
|
30 |
|
31 |
config = PeftConfig.from_pretrained(peft_model_id,
|
32 |
-
use_auth_token="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", load_in_8bit=True, device_map='
|
33 |
|
34 |
-
newmodel = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='
|
35 |
use_auth_token="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")
|
36 |
|
37 |
newtokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path,
|
38 |
-
use_auth_token="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", load_in_8bit=True, device_map='
|
39 |
|
40 |
# Load the Lora model
|
41 |
newmodel = PeftModel.from_pretrained(newmodel, peft_model_id,
|
42 |
-
use_auth_token="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", load_in_8bit=True, device_map='
|
43 |
|
44 |
def givetext(input_text,lmodel,ltokenizer):
|
45 |
eval_prompt_pt1 = "\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction: Act like a therapist and respond\n\n### Input: "
|
@@ -62,7 +62,6 @@ demo.launch()
|
|
62 |
|
63 |
"""
|
64 |
|
65 |
-
|
66 |
import gradio as gr
|
67 |
import torch
|
68 |
from peft import PeftModel, PeftConfig
|
@@ -93,3 +92,5 @@ def mental_chat(message, history):
|
|
93 |
demo = gr.ChatInterface(mental_chat)
|
94 |
|
95 |
demo.launch()
|
|
|
|
|
|
17 |
#!pip install accelerate
|
18 |
#!pip install -i
|
19 |
|
20 |
+
|
21 |
|
22 |
import gradio as gr
|
23 |
import torch
|
|
|
29 |
peft_model_id = "charansr/llama2-7b-chat-hf-therapist"
|
30 |
|
31 |
config = PeftConfig.from_pretrained(peft_model_id,
|
32 |
+
use_auth_token="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", load_in_8bit=True, device_map='cpu',)
|
33 |
|
34 |
+
newmodel = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='cpu',
|
35 |
use_auth_token="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")
|
36 |
|
37 |
newtokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path,
|
38 |
+
use_auth_token="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", load_in_8bit=True, device_map='cpu',)
|
39 |
|
40 |
# Load the Lora model
|
41 |
newmodel = PeftModel.from_pretrained(newmodel, peft_model_id,
|
42 |
+
use_auth_token="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", load_in_8bit=True, device_map='cpu')
|
43 |
|
44 |
def givetext(input_text,lmodel,ltokenizer):
|
45 |
eval_prompt_pt1 = "\nBelow is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction: Act like a therapist and respond\n\n### Input: "
|
|
|
62 |
|
63 |
"""
|
64 |
|
|
|
65 |
import gradio as gr
|
66 |
import torch
|
67 |
from peft import PeftModel, PeftConfig
|
|
|
92 |
demo = gr.ChatInterface(mental_chat)
|
93 |
|
94 |
demo.launch()
|
95 |
+
|
96 |
+
"""
|