01-ai/yi-34b 🔢📝 → 📝

▶️ 3.7K runs 📅 Nov 2023 ⚙️ Cog 0.8.6 🔗 GitHub ⚖️ License
code-generation question-answering text-generation

About

The Yi series models are large language models trained from scratch by developers at 01.AI.

Example Output

Prompt:

"Some great names for dogs are:"

Output

1.Lobo
2.Santana
3.Juice
4.Pearl
5.Pepper
6.Cash
7.Jager
8.Beer
9.Jack
10.Lucky
11.Beau
12.Boo
13.Dude
14.Cocoa
15.Piggy
16.Gypsy
17.Mocha
18.Lucy
19.Bud
20.Chi
21.ChiChi
22.M

Performance Metrics

4.67s Prediction Time
4.71s Total Time
All Input Parameters 
{
  "top_k": 50,
  "top_p": 0.95,
  "prompt": "Some great names for dogs are:",
  "temperature": 0.8,
  "max_new_tokens": 128,
  "prompt_template": "{prompt}",
  "presence_penalty": 0,
  "frequency_penalty": 0
}
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: 0.95
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 (required) Type: string
temperature Type: numberDefault: 0.8
The value used to modulate the next token probabilities.
max_new_tokens Type: integerDefault: 512
The maximum number of tokens the model should generate as output.
prompt_template Type: stringDefault: {prompt}
The template used to format the prompt. The input prompt is inserted into the template using the `{prompt}` placeholder.
presence_penalty Type: numberDefault: 0
Presence penalty
frequency_penalty Type: numberDefault: 0
Frequency penalty
Output Schema

Output

Type: array • Items Type: string

Example Execution Logs 
Generated 128 tokens in 4.597692012786865 seconds.
Version Details
Version ID
d83ccf090ccd5c7fe507ca302a558a850468293385d02bb807ee2753d802dd85
Version Created
November 14, 2023
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