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⭐ Official ▶️ 161.8M runs 📅 Apr 2024 ⚙️ Cog 0.9.4 🔗 GitHub ⚖️ License

code-generation question-answering text-generation text-translation

About

A 70 billion parameter language model from Meta, fine tuned for chat completions

Example Output

Prompt:

Work through this problem step by step:

Q: Sarah has 7 llamas. Her friend gives her 3 more trucks of llamas. Each truck has 5 llamas. How many llamas does Sarah have in total?

Output

Let's break this problem down step by step.

Step 1: Sarah already has 7 llamas.

Step 2: Her friend gives her 3 trucks of llamas. We need to find out how many llamas are in these 3 trucks.

Step 3: Each truck has 5 llamas, so we multiply the number of trucks (3) by the number of llamas per truck (5):

3 trucks x 5 llamas/truck = 3 x 5 = 15 llamas

Step 4: Sarah already had 7 llamas, and now she gets 15 more llamas from her friend. To find the total number of llamas Sarah has, we add the two numbers together:

7 llamas (already had) + 15 llamas (from her friend) = 22 llamas

Therefore, Sarah has a total of 22 llamas.

Performance Metrics

4.05s Prediction Time

3.47s Total Time

All Input Parameters

{
  "top_p": 0.9,
  "prompt": "Work through this problem step by step:\n\nQ: Sarah has 7 llamas. Her friend gives her 3 more trucks of llamas. Each truck has 5 llamas. How many llamas does Sarah have in total?",
  "max_tokens": 512,
  "min_tokens": 0,
  "temperature": 0.6,
  "prompt_template": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
  "presence_penalty": 1.15,
  "frequency_penalty": 0.2
}

Input Parameters

top_k Type: integerDefault: 50: 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 Type: numberDefault: 0.9: 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).
prompt Type: stringDefault:: Prompt
max_tokens Type: integerDefault: 512: The maximum number of tokens the model should generate as output.
min_tokens Type: integerDefault: 0: The minimum number of tokens the model should generate as output.
temperature Type: numberDefault: 0.6: The value used to modulate the next token probabilities.
prompt_template Type: stringDefault: {prompt}: Prompt template. The string `{prompt}` will be substituted for the input prompt. If you want to generate dialog output, use this template as a starting point and construct the prompt string manually, leaving `prompt_template={prompt}`.
presence_penalty Type: numberDefault: 1.15: Presence penalty
frequency_penalty Type: numberDefault: 0.2: Frequency penalty

Output Schema

Output

Type: array • Items Type: string

Version Details

Version ID: fbfb20b472b2f3bdd101412a9f70a0ed4fc0ced78a77ff00970ee7a2383c575d
Version Created: April 17, 2024

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