sentiment-model-imdb

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Daksh0505

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Quick Summary

This repository contains two deep learning models for sentiment classification of IMDB movie reviews, each trained with a different vocabulary size and number of parameters.

Code Examples

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

🔧 Load Models & Tokenizers (from Hugging Face Hub)python

from huggingface_hub import hf_hub_download
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.text import tokenizer_from_json
import json

# === Model A ===
model_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_6.6M.keras")
tokenizer_path_a = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_50k.json")

with open(tokenizer_path_a, "r") as f:
    tokenizer_a = tokenizer_from_json(json.load(f))

model_a = load_model(model_path_a)

# === Model B ===
model_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="sentiment_model_imdb_34M.keras")
tokenizer_path_b = hf_hub_download(repo_id="Daksh0505/sentiment-model-imdb", filename="tokenizer_256k.json")

with open(tokenizer_path_b, "r") as f:
    tokenizer_b = tokenizer_from_json(json.load(f))

model_b = load_model(model_path_b)

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