Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,43 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
pip -q install langchain huggingface_hub transformers sentence_transformers accelerate bitsandbytes
|
2 |
+
|
3 |
+
import os
|
4 |
+
os.environ['HUGGINGFACEHUB_API_TOKEN'] = prompttoken
|
5 |
+
|
6 |
+
from langchain import PromptTemplate, HuggingFaceHub, LLMChain
|
7 |
+
|
8 |
+
template = """Question: {question}
|
9 |
+
Answer: Let's think step by step."""
|
10 |
+
|
11 |
+
prompt = PromptTemplate(template=template, input_variables=["question"])
|
12 |
+
|
13 |
+
llm_chain = LLMChain(prompt=prompt,
|
14 |
+
llm=HuggingFaceHub(repo_id="google/flan-t5-xl",
|
15 |
+
model_kwargs={"temperature":0,
|
16 |
+
"max_length":64}))
|
17 |
+
|
18 |
+
|
19 |
+
from langchain.llms import HuggingFacePipeline
|
20 |
+
import torch
|
21 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline, AutoModelForSeq2SeqLM, AutoTokenizer, AutoModelForSeq2SeqLM
|
22 |
+
|
23 |
+
model_id = 'Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum'
|
24 |
+
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
25 |
+
model = AutoModelForSeq2SeqLM.from_pretrained(model_id, from_tf=True)
|
26 |
+
|
27 |
+
pipeline = pipeline(
|
28 |
+
"text2text-generation",
|
29 |
+
model=model,
|
30 |
+
tokenizer=tokenizer,
|
31 |
+
max_length=128
|
32 |
+
)
|
33 |
+
|
34 |
+
local_llm = HuggingFacePipeline(pipeline=pipeline)
|
35 |
+
|
36 |
+
|
37 |
+
llm_chain = LLMChain(prompt=prompt,
|
38 |
+
llm=local_llm
|
39 |
+
)
|
40 |
+
|
41 |
+
question = "Excel Sheet"
|
42 |
+
|
43 |
+
print(llm_chain.run(question))
|