Claude Code Forge enables operations teams to set up scripts for using TensorBlock Forge with Claude Code. This allows access to any AI model through Claude's interface, streamlining AI model integration and management.
git clone https://github.com/TensorBlock/claude-code-forge.gitClaude Code Forge enables operations teams to set up scripts for using TensorBlock Forge with Claude Code. This allows access to any AI model through Claude's interface, streamlining AI model integration and management.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/TensorBlock/claude-code-forgeCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Set up a script for using TensorBlock Forge with Claude Code to integrate [AI_MODEL_NAME] for [SPECIFIC_USE_CASE]. The script should include authentication, API calls, and error handling. Ensure it's compatible with [OPERATING_SYSTEM] and can be scheduled to run [FREQUENCY].
Here's a Python script for integrating the Hugging Face Transformers model with TensorBlock Forge via Claude Code. The script authenticates using your API key, makes a request to the Hugging Face API, processes the response, and handles potential errors. It's designed for Linux and can be scheduled to run daily.
```python
import requests
import json
import os
from datetime import datetime
# Authentication
API_KEY = os.getenv('CLAUDE_API_KEY')
HEADERS = {'Authorization': f'Bearer {API_KEY}'}
# Configuration
MODEL_NAME = 'Hugging Face Transformers'
USE_CASE = 'Text Generation'
ENDPOINT = 'https://api.huggingface.co/models'
# Function to call the API
def call_ai_model(prompt):
data = {
'inputs': prompt,
'parameters': {
'max_length': 50,
'num_return_sequences': 1
}
}
response = requests.post(f'{ENDPOINT}/{MODEL_NAME}', headers=HEADERS, json=data)
return response.json()
# Main function
def main():
try:
prompt = 'Generate a creative story about a robot discovering humanity.'
result = call_ai_model(prompt)
print(f'Result at {datetime.now()}: {result}')
except Exception as e:
print(f'Error: {e}')
if __name__ == '__main__':
main()
```
This script can be scheduled to run daily using cron jobs on Linux.Recover up to 99% of import fees with no upfront costs
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