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Configuration error
Configuration error
[91mโ Error occurred at line 76: python3 - <<EOF | |
from transformers import AutoTokenizer, AutoModelForCausalLM | |
print("๐ Downloading tokenizer & model...") | |
tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME") | |
model = AutoModelForCausalLM.from_pretrained("$MODEL_NAME") | |
print("โ Model ready.") | |
EOF | |
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[91mโ Error occurred at line 76: python3 - <<EOF | |
from transformers import AutoTokenizer, GPTNeoForCausalLM | |
print("๐ Downloading tokenizer & model (GPTNeoForCausalLM)...") | |
tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME") | |
model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME") | |
print("โ Model ready (GPTNeoForCausalLM).") | |
EOF | |
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[91mโ Error occurred at line 76: python3 - <<EOF | |
from transformers import AutoTokenizer, GPTNeoForCausalLM | |
print("๐ Downloading tokenizer & model (GPTNeoForCausalLM)...") | |
tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME") | |
model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME") | |
print("โ Model ready (GPTNeoForCausalLM).") | |
EOF | |
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[91mโ Error occurred at line 74: python3 - <<EOF | |
from transformers import AutoTokenizer, GPTNeoForCausalLM | |
print("๐ Downloading tokenizer & model (GPTNeoForCausalLM)...") | |
tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME") | |
model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME") | |
print("โ Model ready (GPTNeoForCausalLM).") | |
EOF | |
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[91mโ Error occurred at line 88: python3 - <<EOF | |
from transformers import GPT2Tokenizer, GPTNeoForCausalLM | |
print("๐ Downloading tokenizer & model (GPTNeoForCausalLM)...") | |
tokenizer = GPT2Tokenizer.from_pretrained("$MODEL_NAME") | |
model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME") | |
print("โ Model ready (GPTNeoForCausalLM).") | |
EOF | |
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[91mโ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space --space-sdks gradio[0m | |
[91mโ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space[0m | |
[91mโ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space[0m | |
[91mโ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space[0m | |
[91mโ Error occurred at line 182: huggingface-cli repo create "$HF_SPACE_NAME" --type space[0m | |
[91mโ Error occurred at line 216: huggingface-cli repo create "$HF_SPACE_NAME" --type space --space-sdk gradio[0m | |
[91mโ Error occurred at line 184: python3 - <<EOF | |
from transformers import GPT2Tokenizer, GPTNeoForCausalLM | |
import json | |
# Load configuration | |
with open("$WORK_DIR/shx-config.json", "r") as f: | |
config = json.load(f) | |
tokenizer = GPT2Tokenizer.from_pretrained(config["model_name"]) | |
model = GPTNeoForCausalLM.from_pretrained(config["model_name"]) | |
prompt = "SHX is" | |
inputs = tokenizer(prompt, return_tensors="pt", padding=True) | |
output = model.generate( | |
input_ids=inputs.input_ids, | |
attention_mask=inputs.attention_mask, | |
pad_token_id=tokenizer.eos_token_id, | |
max_length=config["max_length"], | |
temperature=config["temperature"], | |
top_k=config["top_k"], | |
top_p=config["top_p"] | |
) | |
print("๐ง SHX Test Output:", tokenizer.decode(output[0], skip_special_tokens=True)) | |
EOF | |
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[91mโ Error occurred at line 168: cat <<EOF > "$WORK_DIR/README.md" | |
--- | |
title: SHX-Auto GPT Space | |
emoji: ๐ง | |
colorFrom: gray | |
colorTo: blue | |
sdk: gradio | |
sdk_version: "3.50.2" | |
app_file: app.py | |
pinned: true | |
--- | |
# ๐ SHX-Auto: Hyperintelligent Neural Interface | |
> Built on **[EleutherAI/gpt-neo-1.3](https://huggingface.co/EleutherAI/gpt-neo-1.3)** | |
> Powered by โก Gradio + Hugging Face Spaces + Quantum-AI Concepts | |
--- | |
## ๐งฌ Purpose | |
SHX-Auto is a **self-evolving AI agent** designed to generate full-stack solutions, SaaS, and code with real-time inference using the `EleutherAI/gpt-neo-1.3` model. It is a powerful tool for quantum-native developers, enabling them to build and automate complex systems with ease. | |
## ๐ง Model Used | |
- **Model:** [`EleutherAI/gpt-neo-1.3`](https://huggingface.co/EleutherAI/gpt-neo-1.3) | |
- **Architecture:** Transformer Decoder | |
- **Training Data:** The Pile (825GB diverse dataset) | |
- **Use Case:** Conversational AI, Code Generation, SaaS Bootstrapping | |
--- | |
## ๐ฎ How to Use | |
Interact with SHX below ๐ | |
Type in English โ it auto-generates: | |
- โ Python Code | |
- โ Websites / HTML / CSS / JS | |
- โ SaaS / APIs | |
- โ AI Agent Logic | |
--- | |
## โ๏ธ Technologies | |
- โ๏ธ GPT-Neo 1.3B | |
- ๐ง SHX Agent Core | |
- ๐ Gradio SDK 3.50.2 | |
- ๐ Python 3.10 | |
- ๐ Hugging Face Spaces | |
--- | |
## ๐ Getting Started | |
### Overview | |
SHX-Auto is a powerful, GPT-Neo-based terminal agent designed to assist quantum-native developers in building and automating complex systems. With its advanced natural language processing capabilities, SHX-Auto can understand and execute a wide range of commands, making it an indispensable tool for developers. | |
### Features | |
- **Advanced NLP**: Utilizes the EleutherAI/gpt-neo-1.3 model for sophisticated language understanding and generation. | |
- **Gradio Interface**: User-friendly interface for interacting with the model. | |
- **Customizable Configuration**: Easily adjust model parameters such as temperature, top_k, and top_p. | |
- **Real-time Feedback**: Get immediate responses to your commands and see the chat history. | |
### Usage | |
1. **Initialize the Space**: | |
- Clone the repository or create a new Space on Hugging Face. | |
- Ensure you have the necessary dependencies installed. | |
2. **Run the Application**: | |
- Use the Gradio interface to interact with SHX-Auto. | |
- Enter your commands in the input box and click "Run" to get responses. | |
### Configuration | |
- **Model Name**: `EleutherAI/gpt-neo-1.3` | |
- **Max Length**: 150 | |
- **Temperature**: 0.7 | |
- **Top K**: 50 | |
- **Top P**: 0.9 | |
### Example | |
```python | |
# Example command | |
prompt = "Create a simple web application with a form to collect user data." | |
response = shx_terminal(prompt) | |
print(f"๐ค SHX Response: {response}") | |
Final Steps | |
Initialize git in this folder: | |
git init | |
Commit your SHX files: | |
git add . && git commit -m "Initial SHX commit" | |
Create the Space manually (choose SDK: gradio/static/etc): | |
huggingface-cli repo create SHX-Auto --type space --space-sdk gradio | |
Add remote: | |
git remote add origin https://huggingface.co/spaces/$HF_USERNAME/SHX-Auto | |
Push your space: | |
git branch -M main && git push -u origin main | |
๐ After that, visit: https://huggingface.co/spaces/$HF_USERNAME/SHX-Auto | |
SHX interface will now be live on Hugging Face. HAPPY CODING! | |
For more information and support, visit our GitHub repository: | |
https://github.com/subatomicERROR | |
EOF | |
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