Initial deployment

.gitattributes copy

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
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+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
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+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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Dockerfile

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+# Dockerfile
+FROM python:3.10-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y git-lfs && apt-get clean
+
+# Install Python dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt && \
+    python -m spacy download en_core_web_sm
+
+# Copy application code and model
+COPY main.py .
+COPY config.json .
+COPY model.safetensors .
+COPY tokenizer_config.json .
+COPY vocab.json .
+COPY merges.txt .
+COPY generation_config.json .
+COPY special_tokens_map.json .
+
+# Fix permissions
+RUN chmod -R 755 /app
+
+EXPOSE 7860
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

README copy.md

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+---
+title: SloganGenerator
+emoji: 🐢
+colorFrom: pink
+colorTo: yellow
+sdk: docker
+pinned: false
+license: mit
+short_description: api setup for "Slogyn" project
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

config.json

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+{
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 1024,
+  "n_head": 16,
+  "n_inner": null,
+  "n_layer": 24,
+  "n_positions": 1024,
+  "n_special": 0,
+  "predict_special_tokens": true,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4",
+  "use_cache": true,
+  "vocab_size": 50257
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.49.0"
+}

main.py

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+# main.py
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from typing import Optional
+from transformers import GPT2LMHeadModel, GPT2Tokenizer, pipeline
+import torch
+import spacy
+
+# Initialize FastAPI app
+app = FastAPI()
+
+# Configure CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Pydantic model for request body
+class SloganRequest(BaseModel):
+    brand: str
+    description: str
+    industry: str
+    tone: Optional[str] = "playful"
+    num: Optional[int] = 5
+    liked_slogan: Optional[str] = None
+
+# Load models
+nlp = spacy.load("en_core_web_sm")
+model = GPT2LMHeadModel.from_pretrained("./") #slogan_generator_medium")
+tokenizer = GPT2Tokenizer.from_pretrained("./") #slogan_generator_medium")
+generator = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    device=0 if torch.cuda.is_available() else -1
+)
+
+# Tone presets
+TONE_PRESETS = {
+    "playful": {"temperature": 0.95, "top_p": 0.95, "repetition_penalty": 1.2},
+    "bold": {"temperature": 0.8, "top_p": 0.9, "repetition_penalty": 1.45},
+    "minimalist": {"temperature": 0.6, "top_p": 0.8, "repetition_penalty": 1.5},
+    "luxury": {"temperature": 0.7, "top_p": 0.85, "repetition_penalty": 1.35},
+    "classic": {"temperature": 0.7, "top_p": 0.9, "repetition_penalty": 1.25}
+}
+
+def summarize_description(text: str) -> str:
+    """Extract key words from description using spaCy"""
+    doc = nlp(text)
+    keywords = [token.text for token in doc if token.pos_ in ["NOUN", "PROPN", "ADJ"]]
+    return " ".join(keywords[:12])
+
+@app.post("/generate-slogans")
+async def generate_slogans(request: SloganRequest):
+    try:
+        # Process description
+        processed_desc = summarize_description(request.description)
+        
+        # Generate prompts based on presence of liked slogan
+        if request.liked_slogan:
+            prompt1 = (
+                f"Create {request.industry} brand slogans similar to: '{request.liked_slogan}'\n"
+                f"Brand: {request.brand}\n"
+                f"Key Attributes: {processed_desc}\n"
+                "Slogan:"
+            )
+            prompt2 = (
+                f"Generate slogans in the style of: '{request.liked_slogan}'\n"
+                f"For: {request.brand}\n"
+                f"Details: {processed_desc}\n"
+                "Slogan:"
+            )
+        else:
+            prompt1 = (
+                f"Create a {request.industry} brand slogan that's {request.tone} and unique.\n"
+                f"Brand: {request.brand}\n"
+                f"Attributes: {processed_desc}\n"
+                "Slogan:"
+            )
+            prompt2 = (
+                f"Write {request.tone} marketing slogans for this {request.industry} brand:\n"
+                f"Name: {request.brand}\n"
+                f"About: {processed_desc}\n"
+                "Slogan:"
+            )
+
+        # Generation parameters
+        gen_params = {
+            **TONE_PRESETS[request.tone],
+            "max_new_tokens": 25,
+            "num_return_sequences": request.num,
+            "do_sample": True,
+            "pad_token_id": tokenizer.eos_token_id
+        }
+
+        # Generate from both prompts
+        outputs1 = generator(prompt1, **gen_params)
+        outputs2 = generator(prompt2, **gen_params)
+
+        # Process and deduplicate slogans
+        slogans = []
+        for output_group in [outputs1, outputs2]:
+            for o in output_group:
+                raw = o['generated_text'].split("Slogan:")[-1].strip()
+                clean = raw.split("\n")[0].replace('"', '').replace('(', '').split(".")[0].strip()
+                if len(clean) > 4 and clean not in slogans:
+                    slogans.append(clean)
+
+        return {"slogans": slogans[:request.num * 2]}
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f3391b213b99a63f1e56f519fdd7c137970767c4f1b7c4b98957109e28047f59
+size 812602888

requirements.txt

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+# requirements.txt
+fastapi>=0.68.0
+uvicorn>=0.15.0
+transformers>=4.0.0
+torch>=1.8.0
+spacy>=3.7.2
+protobuf>=3.20.0  # Critical fix for build_py_2to3 error
+setuptools==57.5.0  # Temporary workaround if needed
+https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl
+
+#python-multipart

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|endoftext|>",
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "50256": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 1024,
+  "pad_token": "<|endoftext|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}

training_args.bin

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+size 5304