Hotfix llama3
This commit is contained in:
Paul
@@ -4,236 +4,16 @@
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"name": "meta-llama-3-70b-instruct",
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"description": "A 70 billion parameter language model from Meta, fine tuned for chat completions",
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"visibility": "public",
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"github_url": "https://github.com/meta-llama/llama3",
|
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"github_url": null,
|
||||
"paper_url": null,
|
||||
"license_url": "https://github.com/meta-llama/llama3/blob/main/LICENSE",
|
||||
"run_count": 47428809,
|
||||
"cover_image_url": "https://tjzk.replicate.delivery/models_models_cover_image/12ed0c29-9236-4a21-ac5a-7faff3045ab1/meta-logo.png",
|
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"default_example": {
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||||
"id": "7zr9g2asx9rgj0cey8698vm4d4",
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"model": "meta/meta-llama-3-70b-instruct",
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"version": "fbfb20b472b2f3bdd101412a9f70a0ed4fc0ced78a77ff00970ee7a2383c575d",
|
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"status": "succeeded",
|
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"input": {
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"top_p": 0.9,
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"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?",
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"max_tokens": 512,
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"min_tokens": 0,
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"temperature": 0.6,
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"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",
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"presence_penalty": 1.15,
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"frequency_penalty": 0.2
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},
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"output": [
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|
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|
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" problem",
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" step",
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"Step",
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|
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" Sarah",
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"amas",
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"Step",
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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" ll",
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"amas",
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".",
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""
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],
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"logs": "",
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"error": "",
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"metrics": {
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"total_time": 3.47,
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"input_token_count": 54,
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"tokens_per_second": 41.72998441835564,
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"output_token_count": 166,
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"predict_time": 4.045511
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},
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"created_at": "2024-04-18T16:31:19.530000Z",
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"started_at": "2024-04-18T16:31:19Z",
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"completed_at": "2024-04-18T16:31:23Z",
|
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"urls": {
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"stream": "https://streaming-api.svc.us.c.replicate.net/v1/streams/cvg64spwkdzlpdltjkmv6jotmwn2cq5btgxirmsbejvsxx7xp2la",
|
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"get": "https://api.replicate.com/v1/predictions/7zr9g2asx9rgj0cey8698vm4d4",
|
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"cancel": "https://api.replicate.com/v1/predictions/7zr9g2asx9rgj0cey8698vm4d4/cancel"
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}
|
||||
},
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"license_url": null,
|
||||
"run_count": 0,
|
||||
"cover_image_url": null,
|
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"default_example": null,
|
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"latest_version": {
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||||
"id": "fbfb20b472b2f3bdd101412a9f70a0ed4fc0ced78a77ff00970ee7a2383c575d",
|
||||
"created_at": "2024-04-17T21:58:54.806446+00:00",
|
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"cog_version": "0.9.4",
|
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"id": "2ce90869e475b267cdbb7f2b74b00851c0f3307edda4bde88eb88085832d891e",
|
||||
"created_at": "2024-06-19T19:19:18.233909+00:00",
|
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"cog_version": "0.10.0-alpha13",
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"openapi_schema": {
|
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"info": {
|
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"title": "Cog",
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@@ -258,24 +38,6 @@
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"operationId": "root__get"
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}
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},
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"/ready": {
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"get": {
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"summary": "Ready",
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"responses": {
|
||||
"200": {
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"title": "Response Ready Ready Get"
|
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}
|
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}
|
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},
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"description": "Successful Response"
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}
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},
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"operationId": "ready_ready_get"
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}
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},
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"/shutdown": {
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"post": {
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"summary": "Start Shutdown",
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@@ -472,69 +234,105 @@
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"Input": {
|
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"type": "object",
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||||
"title": "Input",
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"required": [
|
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"prompt"
|
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],
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"properties": {
|
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"seed": {
|
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"type": "integer",
|
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"title": "Seed",
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"x-order": 10,
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"description": "Random seed. Leave blank to randomize the seed."
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},
|
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"top_k": {
|
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"type": "integer",
|
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"title": "Top K",
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"default": 50,
|
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"x-order": 5,
|
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"description": "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)."
|
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"default": 0,
|
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"minimum": -1,
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"x-order": 6,
|
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"description": "When decoding text, samples from the top k most likely tokens; lower to ignore less likely tokens."
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},
|
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"top_p": {
|
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"type": "number",
|
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"title": "Top P",
|
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"default": 0.9,
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"x-order": 4,
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"description": "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)."
|
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"default": 0.95,
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"maximum": 1,
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"minimum": 0,
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"x-order": 5,
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"description": "When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens."
|
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},
|
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"prompt": {
|
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"type": "string",
|
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"title": "Prompt",
|
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"default": "",
|
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"x-order": 0,
|
||||
"description": "Prompt"
|
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"description": "Prompt to send to the model."
|
||||
},
|
||||
"max_tokens": {
|
||||
"type": "integer",
|
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"title": "Max Tokens",
|
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"default": 512,
|
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"minimum": 1,
|
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"x-order": 2,
|
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"description": "The maximum number of tokens the model should generate as output."
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"description": "Maximum number of tokens to generate. A word is generally 2-3 tokens."
|
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},
|
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"min_tokens": {
|
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"type": "integer",
|
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"title": "Min Tokens",
|
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"default": 0,
|
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"x-order": 1,
|
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"description": "The minimum number of tokens the model should generate as output."
|
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"minimum": -1,
|
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"x-order": 3,
|
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"description": "Minimum number of tokens to generate. To disable, set to -1. A word is generally 2-3 tokens."
|
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},
|
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"temperature": {
|
||||
"type": "number",
|
||||
"title": "Temperature",
|
||||
"default": 0.6,
|
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"x-order": 3,
|
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"description": "The value used to modulate the next token probabilities."
|
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"default": 0.7,
|
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"maximum": 5,
|
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"minimum": 0,
|
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"x-order": 4,
|
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"description": "Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value."
|
||||
},
|
||||
"system_prompt": {
|
||||
"type": "string",
|
||||
"title": "System Prompt",
|
||||
"default": "You are a helpful assistant",
|
||||
"x-order": 1,
|
||||
"description": "System prompt to send to the model. This is prepended to the prompt and helps guide system behavior."
|
||||
},
|
||||
"length_penalty": {
|
||||
"type": "number",
|
||||
"title": "Length Penalty",
|
||||
"default": 1,
|
||||
"maximum": 5,
|
||||
"minimum": 0,
|
||||
"x-order": 8,
|
||||
"description": "A parameter that controls how long the outputs are. If < 1, the model will tend to generate shorter outputs, and > 1 will tend to generate longer outputs."
|
||||
},
|
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"stop_sequences": {
|
||||
"type": "string",
|
||||
"title": "Stop Sequences",
|
||||
"default": "<|end_of_text|>,<|eot_id|>",
|
||||
"x-order": 7,
|
||||
"description": "A comma-separated list of sequences to stop generation at. For example, '<end>,<stop>' will stop generation at the first instance of 'end' or '<stop>'."
|
||||
},
|
||||
"prompt_template": {
|
||||
"type": "string",
|
||||
"title": "Prompt Template",
|
||||
"default": "{prompt}",
|
||||
"x-order": 8,
|
||||
"description": "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}`."
|
||||
"default": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>",
|
||||
"x-order": 11,
|
||||
"description": "Template for formatting the prompt. Can be an arbitrary string, but must contain the substring `{prompt}`."
|
||||
},
|
||||
"presence_penalty": {
|
||||
"type": "number",
|
||||
"title": "Presence Penalty",
|
||||
"default": 1.15,
|
||||
"x-order": 6,
|
||||
"description": "Presence penalty"
|
||||
"default": 0,
|
||||
"x-order": 9,
|
||||
"description": "A parameter that penalizes repeated tokens regardless of the number of appearances. As the value increases, the model will be less likely to repeat tokens in the output."
|
||||
},
|
||||
"frequency_penalty": {
|
||||
"type": "number",
|
||||
"title": "Frequency Penalty",
|
||||
"default": 0.2,
|
||||
"x-order": 7,
|
||||
"description": "Frequency penalty"
|
||||
"log_performance_metrics": {
|
||||
"type": "boolean",
|
||||
"title": "Log Performance Metrics",
|
||||
"default": false,
|
||||
"x-order": 12
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -712,4 +510,4 @@
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -4,204 +4,16 @@
|
||||
"name": "meta-llama-3-8b-instruct",
|
||||
"description": "An 8 billion parameter language model from Meta, fine tuned for chat completions",
|
||||
"visibility": "public",
|
||||
"github_url": "https://github.com/meta-llama/llama3",
|
||||
"github_url": null,
|
||||
"paper_url": null,
|
||||
"license_url": "https://github.com/meta-llama/llama3/blob/main/LICENSE",
|
||||
"run_count": 21431865,
|
||||
"cover_image_url": "https://tjzk.replicate.delivery/models_models_cover_image/927d3fce-75e3-4af9-92da-f537bc34072a/meta-logo.png",
|
||||
"default_example": {
|
||||
"id": "855g9wxd7hrgp0cf7tsv1ewzgc",
|
||||
"model": "replicate-internal/llama-3-8b-instruct-int8-triton",
|
||||
"version": "b63acc3f54e3c08cb3b081f049ebc881420035dfc6db48f554530e9c4bc02ba3",
|
||||
"status": "succeeded",
|
||||
"input": {
|
||||
"top_p": 0.95,
|
||||
"prompt": "Johnny has 8 billion parameters. His friend Tommy has 70 billion parameters. What does this mean when it comes to speed?",
|
||||
"temperature": 0.7,
|
||||
"system_prompt": "You are a helpful assistant",
|
||||
"length_penalty": 1,
|
||||
"max_new_tokens": 512,
|
||||
"stop_sequences": "<|end_of_text|>,<|eot_id|>",
|
||||
"prompt_template": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{system_prompt}<|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": 0
|
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},
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||||
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||||
" which",
|
||||
" can",
|
||||
" impact",
|
||||
" system",
|
||||
" performance",
|
||||
".\n\n",
|
||||
"However",
|
||||
",",
|
||||
" it",
|
||||
"'s",
|
||||
" worth",
|
||||
" noting",
|
||||
" that",
|
||||
" the",
|
||||
" relationship",
|
||||
" between",
|
||||
" the",
|
||||
" number",
|
||||
" of",
|
||||
" parameters",
|
||||
" and",
|
||||
" speed",
|
||||
" is",
|
||||
" not",
|
||||
" always",
|
||||
" linear",
|
||||
".",
|
||||
" Other",
|
||||
" factors",
|
||||
",",
|
||||
" such",
|
||||
" as",
|
||||
":\n\n",
|
||||
"*",
|
||||
" Model",
|
||||
" architecture",
|
||||
"\n",
|
||||
"*",
|
||||
" Optim",
|
||||
"izer",
|
||||
" choice",
|
||||
"\n",
|
||||
"*",
|
||||
" Hyper",
|
||||
"parameter",
|
||||
" tuning",
|
||||
"\n\n",
|
||||
"can",
|
||||
" also",
|
||||
" impact",
|
||||
" the",
|
||||
" speed",
|
||||
" of",
|
||||
" a",
|
||||
" neural",
|
||||
" network",
|
||||
".\n\n",
|
||||
"In",
|
||||
" the",
|
||||
" case",
|
||||
" of",
|
||||
" Johnny",
|
||||
" and",
|
||||
" Tommy",
|
||||
",",
|
||||
" it",
|
||||
"'s",
|
||||
" difficult",
|
||||
" to",
|
||||
" say",
|
||||
" which",
|
||||
" one",
|
||||
"'s",
|
||||
" model",
|
||||
" will",
|
||||
" be",
|
||||
" faster",
|
||||
" without",
|
||||
" more",
|
||||
" information",
|
||||
" about",
|
||||
" the",
|
||||
" models",
|
||||
" themselves",
|
||||
"."
|
||||
],
|
||||
"logs": "Random seed used: `57440`\nNote: Random seed will not impact output if greedy decoding is used.\nFormatted prompt: `<|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\nJohnny has 8 billion parameters. His friend Tommy has 70 billion parameters. What does this mean when it comes to speed?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n`Random seed used: `57440`\nNote: Random seed will not impact output if greedy decoding is used.\nFormatted prompt: `<|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\nJohnny has 8 billion parameters. His friend Tommy has 70 billion parameters. What does this mean when it comes to speed?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n`",
|
||||
"error": null,
|
||||
"metrics": {
|
||||
"total_time": 1.657073,
|
||||
"input_token_count": 39,
|
||||
"tokens_per_second": 92.80206135476371,
|
||||
"output_token_count": 149,
|
||||
"predict_time": 1.652461,
|
||||
"time_to_first_token": 0.060728942999999994
|
||||
},
|
||||
"created_at": "2024-05-03T13:45:13.788000Z",
|
||||
"started_at": "2024-05-03T13:45:13.792612Z",
|
||||
"completed_at": "2024-05-03T13:45:15.445073Z",
|
||||
"urls": {
|
||||
"stream": "https://streaming-api.svc.us.c.replicate.net/v1/streams/hscsfwedhigbbnorfpq7c4i3lbac5srhaqgvb4b5m2iuof3rotwq",
|
||||
"get": "https://api.replicate.com/v1/predictions/855g9wxd7hrgp0cf7tsv1ewzgc",
|
||||
"cancel": "https://api.replicate.com/v1/predictions/855g9wxd7hrgp0cf7tsv1ewzgc/cancel"
|
||||
}
|
||||
},
|
||||
"license_url": null,
|
||||
"run_count": 0,
|
||||
"cover_image_url": null,
|
||||
"default_example": null,
|
||||
"latest_version": {
|
||||
"id": "5a6809ca6288247d06daf6365557e5e429063f32a21146b2a807c682652136b8",
|
||||
"created_at": "2024-04-17T21:58:45.726276+00:00",
|
||||
"cog_version": "0.9.4",
|
||||
"id": "b63acc3f54e3c08cb3b081f049ebc881420035dfc6db48f554530e9c4bc02ba3",
|
||||
"created_at": "2024-04-19T21:06:45.886873+00:00",
|
||||
"cog_version": "0.10.0-alpha5",
|
||||
"openapi_schema": {
|
||||
"info": {
|
||||
"title": "Cog",
|
||||
@@ -226,24 +38,6 @@
|
||||
"operationId": "root__get"
|
||||
}
|
||||
},
|
||||
"/ready": {
|
||||
"get": {
|
||||
"summary": "Ready",
|
||||
"responses": {
|
||||
"200": {
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"title": "Response Ready Ready Get"
|
||||
}
|
||||
}
|
||||
},
|
||||
"description": "Successful Response"
|
||||
}
|
||||
},
|
||||
"operationId": "ready_ready_get"
|
||||
}
|
||||
},
|
||||
"/shutdown": {
|
||||
"post": {
|
||||
"summary": "Start Shutdown",
|
||||
@@ -440,69 +234,84 @@
|
||||
"Input": {
|
||||
"type": "object",
|
||||
"title": "Input",
|
||||
"required": [
|
||||
"prompt"
|
||||
],
|
||||
"properties": {
|
||||
"seed": {
|
||||
"type": "integer",
|
||||
"title": "Seed",
|
||||
"x-order": 10,
|
||||
"description": "Random seed. Leave blank to randomize the seed"
|
||||
},
|
||||
"top_k": {
|
||||
"type": "integer",
|
||||
"title": "Top K",
|
||||
"default": 50,
|
||||
"x-order": 5,
|
||||
"description": "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)."
|
||||
"default": 0,
|
||||
"minimum": -1,
|
||||
"x-order": 6,
|
||||
"description": "When decoding text, samples from the top k most likely tokens; lower to ignore less likely tokens"
|
||||
},
|
||||
"top_p": {
|
||||
"type": "number",
|
||||
"title": "Top P",
|
||||
"default": 0.9,
|
||||
"x-order": 4,
|
||||
"description": "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)."
|
||||
"default": 0.95,
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"x-order": 5,
|
||||
"description": "When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens"
|
||||
},
|
||||
"prompt": {
|
||||
"type": "string",
|
||||
"title": "Prompt",
|
||||
"default": "",
|
||||
"x-order": 0,
|
||||
"description": "Prompt"
|
||||
},
|
||||
"max_tokens": {
|
||||
"type": "integer",
|
||||
"title": "Max Tokens",
|
||||
"default": 512,
|
||||
"x-order": 2,
|
||||
"description": "The maximum number of tokens the model should generate as output."
|
||||
},
|
||||
"min_tokens": {
|
||||
"type": "integer",
|
||||
"title": "Min Tokens",
|
||||
"default": 0,
|
||||
"x-order": 1,
|
||||
"description": "The minimum number of tokens the model should generate as output."
|
||||
"description": "Prompt to send to the model."
|
||||
},
|
||||
"temperature": {
|
||||
"type": "number",
|
||||
"title": "Temperature",
|
||||
"default": 0.6,
|
||||
"x-order": 3,
|
||||
"description": "The value used to modulate the next token probabilities."
|
||||
"default": 0.7,
|
||||
"maximum": 5,
|
||||
"minimum": 0,
|
||||
"x-order": 4,
|
||||
"description": "Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value."
|
||||
},
|
||||
"system_prompt": {
|
||||
"type": "string",
|
||||
"title": "System Prompt",
|
||||
"default": "You are a helpful assistant",
|
||||
"x-order": 1,
|
||||
"description": "System prompt to send to the model. This is prepended to the prompt and helps guide system behavior."
|
||||
},
|
||||
"length_penalty": {
|
||||
"type": "number",
|
||||
"title": "Length Penalty",
|
||||
"default": 1,
|
||||
"maximum": 5,
|
||||
"minimum": 0,
|
||||
"x-order": 8,
|
||||
"description": "A parameter that controls how long the outputs are. If < 1, the model will tend to generate shorter outputs, and > 1 will tend to generate longer outputs."
|
||||
},
|
||||
"stop_sequences": {
|
||||
"type": "string",
|
||||
"title": "Stop Sequences",
|
||||
"default": "<|end_of_text|>,<|eot_id|>",
|
||||
"x-order": 7,
|
||||
"description": "A comma-separated list of sequences to stop generation at. For example, '<end>,<stop>' will stop generation at the first instance of 'end' or '<stop>'."
|
||||
},
|
||||
"prompt_template": {
|
||||
"type": "string",
|
||||
"title": "Prompt Template",
|
||||
"default": "{prompt}",
|
||||
"x-order": 8,
|
||||
"description": "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}`."
|
||||
"default": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
|
||||
"x-order": 11,
|
||||
"description": "Template for formatting the prompt. Can be an arbitrary string, but must contain the substring `{prompt}`."
|
||||
},
|
||||
"presence_penalty": {
|
||||
"type": "number",
|
||||
"title": "Presence Penalty",
|
||||
"default": 1.15,
|
||||
"x-order": 6,
|
||||
"description": "Presence penalty"
|
||||
},
|
||||
"frequency_penalty": {
|
||||
"type": "number",
|
||||
"title": "Frequency Penalty",
|
||||
"default": 0.2,
|
||||
"x-order": 7,
|
||||
"description": "Frequency penalty"
|
||||
"default": 0,
|
||||
"x-order": 9,
|
||||
"description": "A parameter that penalizes repeated tokens regardless of the number of appearances. As the value increases, the model will be less likely to repeat tokens in the output."
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -680,4 +489,4 @@
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user