tomasmcm/claude2-alpaca-13b 📝🔢 → 📝

▶️ 3.9K runs 📅 Dec 2023 ⚙️ Cog 0.8.6 📄 Paper ⚖️ License

ai-research chatbot language-model natural-language-processing question-answering text-generation

About

Source: umd-zhou-lab/claude2-alpaca-13B ✦ Quant: TheBloke/claude2-alpaca-13B-AWQ ✦ This model is trained by fine-tuning llama-2 with claude2 alpaca data

Example Output

Prompt:

Below is an instruction that describes a task. Write a response that appropriately completes the request.

Instruction:

Generate a haiku about AI.

Response:

Output

Artificial intelligence
Is a powerful technology
That can help us.

Performance Metrics

0.46s Prediction Time

0.49s Total Time

All Input Parameters

{
  "stop": "###",
  "top_k": -1,
  "top_p": 0.95,
  "prompt": "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\nGenerate a haiku about AI.\n\n### Response:\n",
  "max_tokens": 128,
  "temperature": 0.8,
  "presence_penalty": 0,
  "frequency_penalty": 0
}

Input Parameters

stop Type: string: List of strings that stop the generation when they are generated. The returned output will not contain the stop strings.
top_k Type: integerDefault: -1: Integer that controls the number of top tokens to consider. Set to -1 to consider all tokens.
top_p Type: numberDefault: 0.95Range: 0.01 - 1: Float that controls the cumulative probability of the top tokens to consider. Must be in (0, 1]. Set to 1 to consider all tokens.
prompt (required) Type: string: Text prompt to send to the model.
max_tokens Type: integerDefault: 128: Maximum number of tokens to generate per output sequence.
temperature Type: numberDefault: 0.8Range: 0.01 - 5: Float that controls the randomness of the sampling. Lower values make the model more deterministic, while higher values make the model more random. Zero means greedy sampling.
presence_penalty Type: numberDefault: 0Range: -5 - 5: Float that penalizes new tokens based on whether they appear in the generated text so far. Values > 0 encourage the model to use new tokens, while values < 0 encourage the model to repeat tokens.
frequency_penalty Type: numberDefault: 0Range: -5 - 5: Float that penalizes new tokens based on their frequency in the generated text so far. Values > 0 encourage the model to use new tokens, while values < 0 encourage the model to repeat tokens.

Output Schema

Output

Type: string

Example Execution Logs

Processed prompts:   0%|          | 0/1 [00:00<?, ?it/s]
Processed prompts: 100%|██████████| 1/1 [00:00<00:00,  2.23it/s]
Processed prompts: 100%|██████████| 1/1 [00:00<00:00,  2.23it/s]
Generated 16 tokens in 0.44997215270996094 seconds.

Version Details

Version ID: 49b2d4cc082625d10463f56426bd012ebd75c11e3d6c2b54f7532c6ddd46b944
Version Created: December 10, 2023

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