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Only including the pricer-service2.py file

pull/319/head
craigprobus 4 weeks ago
parent
commit
1a25a4432b
  1. 42
      week8/pricer_service2.py

42
week8/pricer_service2.py

@ -5,6 +5,7 @@ from modal import App, Volume, Image
app = modal.App("pricer-service") app = modal.App("pricer-service")
image = Image.debian_slim().pip_install("huggingface", "torch", "transformers", "bitsandbytes", "accelerate", "peft") image = Image.debian_slim().pip_install("huggingface", "torch", "transformers", "bitsandbytes", "accelerate", "peft")
image.add_local_python_source("hello", "llama") #CP: adding here based on Deprecation warnings...
secrets = [modal.Secret.from_name("hf-secret")] secrets = [modal.Secret.from_name("hf-secret")]
# Constants # Constants
@ -12,31 +13,32 @@ secrets = [modal.Secret.from_name("hf-secret")]
GPU = "T4" GPU = "T4"
BASE_MODEL = "meta-llama/Meta-Llama-3.1-8B" BASE_MODEL = "meta-llama/Meta-Llama-3.1-8B"
PROJECT_NAME = "pricer" PROJECT_NAME = "pricer"
HF_USER = "ed-donner" # your HF name here! Or use mine if you just want to reproduce my results. HF_USER = "cproSD" # your HF name here! Or use mine if you just want to reproduce my results.
RUN_NAME = "2024-09-13_13.04.39" RUN_NAME = "2025-04-08_21.52.37"
PROJECT_RUN_NAME = f"{PROJECT_NAME}-{RUN_NAME}" PROJECT_RUN_NAME = f"{PROJECT_NAME}-{RUN_NAME}"
REVISION = "e8d637df551603dc86cd7a1598a8f44af4d7ae36"
FINETUNED_MODEL = f"{HF_USER}/{PROJECT_RUN_NAME}" FINETUNED_MODEL = f"{HF_USER}/{PROJECT_RUN_NAME}"
MODEL_DIR = "hf-cache/" #DEL: MODEL_DIR = "/models/"
BASE_DIR = MODEL_DIR + BASE_MODEL #DEL: BASE_DIR = MODEL_DIR + BASE_MODEL
FINETUNED_DIR = MODEL_DIR + FINETUNED_MODEL #DEL: FINETUNED_DIR = MODEL_DIR + FINETUNED_MODEL
CACHE_DIR = "/cache" #CP: Use the standard /cache path for hf-hub-cache
QUESTION = "How much does this cost to the nearest dollar?" QUESTION = "How much does this cost to the nearest dollar?"
PREFIX = "Price is $" PREFIX = "Price is $"
@app.cls(image=image, secrets=secrets, gpu=GPU, timeout=1800) #CP: Use the pre-configured hf-hub-cache Volume...
hf_cache_volume = Volume.from_name("hf-hub-cache")
@app.cls(
image=image.env({"HF_HUB_CACHE": CACHE_DIR}),
secrets=secrets,
gpu=GPU,
timeout=1800,
volumes={CACHE_DIR: hf_cache_volume}
)
class Pricer: class Pricer:
@modal.build()
def download_model_to_folder(self):
from huggingface_hub import snapshot_download
import os
os.makedirs(MODEL_DIR, exist_ok=True)
snapshot_download(BASE_MODEL, local_dir=BASE_DIR)
snapshot_download(FINETUNED_MODEL, revision=REVISION, local_dir=FINETUNED_DIR)
@modal.enter() @modal.enter()
def setup(self): def setup(self):
import os
import torch import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, set_seed from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, set_seed
from peft import PeftModel from peft import PeftModel
@ -50,18 +52,15 @@ class Pricer:
) )
# Load model and tokenizer # Load model and tokenizer
self.tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)
self.tokenizer = AutoTokenizer.from_pretrained(BASE_DIR)
self.tokenizer.pad_token = self.tokenizer.eos_token self.tokenizer.pad_token = self.tokenizer.eos_token
self.tokenizer.padding_side = "right" self.tokenizer.padding_side = "right"
self.base_model = AutoModelForCausalLM.from_pretrained( self.base_model = AutoModelForCausalLM.from_pretrained(
BASE_DIR, BASE_MODEL,
quantization_config=quant_config, quantization_config=quant_config,
device_map="auto" device_map="auto"
) )
self.fine_tuned_model = PeftModel.from_pretrained(self.base_model, FINETUNED_MODEL)
self.fine_tuned_model = PeftModel.from_pretrained(self.base_model, FINETUNED_DIR, revision=REVISION)
@modal.method() @modal.method()
def price(self, description: str) -> float: def price(self, description: str) -> float:
@ -86,4 +85,3 @@ class Pricer:
@modal.method() @modal.method()
def wake_up(self) -> str: def wake_up(self) -> str:
return "ok" return "ok"

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