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#!/usr/bin/env python3
"""
Manual model testing script for Hugging Face Inference API
"""
import requests
import os
import json
def test_model(model_id, prompt="Hello, how are you?"):
"""Test a model on the Hugging Face Inference API."""
token = os.getenv("HF_TOKEN")
if not token:
print("❌ No HF_TOKEN found")
return False
headers = {"Authorization": f"Bearer {token}"}
url = f"https://api-inference.huggingface.co/models/{model_id}"
payload = {
"inputs": prompt,
"parameters": {
"max_new_tokens": 50,
"temperature": 0.1
}
}
try:
print(f"🧪 Testing {model_id}...")
response = requests.post(url, headers=headers, json=payload, timeout=30)
print(f" Status: {response.status_code}")
if response.status_code == 200:
result = response.json()
print(f" ✅ Success: {str(result)[:100]}...")
return True
else:
print(f" ❌ Error: {response.text[:200]}...")
return False
except Exception as e:
print(f" ❌ Exception: {str(e)}")
return False
def main():
"""Test various models to find working ones."""
print("🔍 Testing Hugging Face Models")
print("=" * 50)
# Test models that are commonly available
models_to_test = [
"microsoft/DialoGPT-medium",
"gpt2",
"distilgpt2",
"microsoft/DialoGPT-small",
"facebook/blenderbot-400M-distill",
"Salesforce/codet5-small",
"microsoft/codebert-base",
"bigcode/starcoder",
"codellama/CodeLlama-7b-Instruct-hf",
"defog/sqlcoder-7b-2"
]
working_models = []
for model_id in models_to_test:
if test_model(model_id):
working_models.append(model_id)
print()
print("=" * 50)
print(f"✅ Working models: {len(working_models)}")
for model in working_models:
print(f" - {model}")
if working_models:
print("\n📝 Suggested config/models.yaml:")
print("models:")
for i, model_id in enumerate(working_models[:4], 1):
name = model_id.split("/")[-1].replace("-", "_").replace(".", "_")
print(f""" - name: "{name}"
provider: "huggingface"
model_id: "{model_id}"
params:
max_new_tokens: 512
temperature: 0.1
top_p: 0.9
description: "Working model from Hugging Face"
""")
if __name__ == "__main__":
main()
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