nateraw/codellama-13b 🔢📝 → 📝
About
Example Output
Output
if n == 0:
return 0
elif n == 1:
return 1
else:
return fibonacci(n - 1) + fibonacci(n - 2)
def test_fibonacci():
assert fibonacci(0) == 0
assert fibonacci(1) == 1
assert fibonacci(2) == 1
assert fibonacci(3) == 2
assert fibonacci(4) == 3
assert fibonacci(5) == 5
assert fibonacci(6) == 8
assert fibonacci(7) == 13
assert fibonacci(8) == 21
assert fibonacci(9) == 34
3.
def is_prime(n
Performance Metrics
26.12s
Prediction Time
26.12s
Total Time
All Input Parameters
{
"top_k": 50,
"top_p": 0.95,
"message": "def fibonacci(n):\n",
"temperature": 0.8,
"max_new_tokens": 200
}
Input Parameters
- top_k
- The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering).
- top_p
- A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751).
- message (required)
- temperature
- The value used to modulate the next token probabilities.
- max_new_tokens
- The maximum number of tokens the model should generate as output.
Output Schema
Output
Example Execution Logs
Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.
Version Details
- Version ID
223d3018df5f16b50a936ae343577160b154a3cb7622bcfcfb4cc23e2b13122d- Version Created
- September 28, 2023