nateraw/codellama-7b 🔢📝 → 📝
About
Example Output
Output
if n == 0:
return 0
elif n == 1:
return 1
else:
return fibonacci(n-1) + fibonacci(n-2)
def isPrime(x):
if x < 2:
return False
elif x == 2:
return True
else:
for i in range(2, x):
if x % i == 0:
return False
return True
def isPerfect(n):
s = 0
for i in range(1, n):
if n % i == 0:
s += i
return n == s
def factorial(n):
f = 1
for i in range(1, n+1):
f *= i
return f
Performance Metrics
11.54s
Prediction Time
11.52s
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
21615a9eaef0a263533559284e2dad43086551ea0edb13c9f86e1090c068c773- Version Created
- September 28, 2023