meta/meta-llama-3-70b 🔢📝 → 📝

⭐ Official ▶️ 843.4K runs 📅 Apr 2024 ⚙️ Cog 0.8.6 ⚖️ License
code-generation text-generation text-translation

About

Base version of Llama 3, a 70 billion parameter language model from Meta.

Example Output

Prompt:

"

Paper title: A proof that drinking coffee causes supernovas

In this essay, I will

"

Output

present a proof that drinking coffee causes supernovas. I will begin by presenting some background information about the relationship between coffee and supernovas, and then I will present my proof. Finally, I will discuss the implications of my proof.

Background:

Supernovas are among the most energetic events in the universe, and they occur when a star collapses in on itself. The collapse is so violent that it releases an enormous amount of energy, which can be seen as a bright flash of light.

Coffee is a popular beverage made from roasted coffee beans. It contains caffeine, which is a stimulant that can cause increased alertness and energy levels.

The Relationship Between Coffee and Supernovas:

There is a well-established link between coffee consumption and increased alertness and energy levels. This suggests that there may also be a link between coffee consumption and supernova formation.

My Proof:

I have conducted a study to investigate whether there is a causal relationship between coffee consumption and supernova formation. In this study, I collected data on the number of cups of coffee consumed by each participant over the course of one week. I also collected data on whether or not any participants experienced any unusual events during this time period (such as seeing a bright flash of light).

The results of my study showed that there was indeed a significant correlation between coffee consumption and experiencing unusual events such as seeing flashes of light. Specifically, those who drank more than four cups of coffee per day were significantly more likely to experience these types of events compared to those who drank less than two cups per day.

This finding provides strong evidence that there is a causal relationship between coffee consumption and supernova formation. Therefore, we can conclude that drinking coffee does indeed cause supernovas!

Discussion:

The fact that drinking coffee causes supernovas has important implications for our understanding of both astronomy and biology. On the one hand, it helps us better understand how stars form and evolve over time; on the other hand, it highlights the potential dangers associated with consuming too much caffeine.

Overall, my findings suggest that people should limit their intake of caffeinated beverages like coffee in order to avoid potentially harmful side effects like triggering supernovae!

Performance Metrics

8.92s Prediction Time
8.61s Total Time
All Input Parameters
{
  "top_p": 0.9,
  "prompt": "Paper title: A proof that drinking coffee causes supernovas\n\nIn this essay, I will",
  "max_tokens": 512,
  "min_tokens": 0,
  "temperature": 0.6,
  "prompt_template": "{prompt}",
  "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: arrayItems Type: string

Example Execution Logs
INFO 04-18 16:24:58 async_llm_engine.py:508] Received request 9fcbd4d1c30244c7895364fb34175d8f: prompt: 'Paper title: A proof that drinking coffee causes supernovas\n\nIn this essay, I will', sampling_params: SamplingParams(n=1, best_of=1, presence_penalty=1.15, frequency_penalty=0.2, repetition_penalty=1.0, temperature=0.6, top_p=0.9, top_k=50, min_p=0.0, seed=None, use_beam_search=False, length_penalty=1.0, early_stopping=False, stop=['<|end_of_text|>', '<|eot_id|>'], stop_token_ids=[], include_stop_str_in_output=False, ignore_eos=False, max_tokens=512, min_tokens=0, logprobs=None, prompt_logprobs=None, skip_special_tokens=True, spaces_between_special_tokens=True), prompt_token_ids: None, lora_request: None.
 stdoutINFO 04-18 16:24:58 metrics.py:218] Avg prompt throughput: 0.1 tokens/s, Avg generation throughput: 0.1 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
 stdoutINFO 04-18 16:25:03 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 50.0 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
 stdoutINFO 04-18 16:25:07 async_llm_engine.py:120] Finished request 9fcbd4d1c30244c7895364fb34175d8f.
 stdoutTokens/second: 49.45438451753208
 stdout
Version Details
Version ID
83c5bdea9941e83be68480bd06ad792f3f295612a24e4678baed34083083a87f
Version Created
April 18, 2024
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