Update README.md
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README.md
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@@ -11,7 +11,7 @@ widget:
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different industries, and advice on which qualifications would be
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beneficial for pursuing particular fields.
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- role: user
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content:
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- role: assistant
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content: Hi! How may I help you?
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- role: user
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@@ -22,7 +22,7 @@ widget:
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- role: system
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content: You are a knowledgeable assistant. Help the user as much as you can.
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- role: user
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content: How to become
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- messages:
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- role: system
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content: You are a helpful assistant who provides concise responses.
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@@ -32,8 +32,7 @@ widget:
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content: Hello there! How may I help you?
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- role: user
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content: >-
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I need to
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development?
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- messages:
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- role: system
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content: >-
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@@ -41,11 +40,11 @@ widget:
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should complete with all your knowledge.
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- role: user
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content: >-
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Write the
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-
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inference:
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parameters:
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max_new_tokens:
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penalty_alpha: 0.5
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top_k: 4
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base_model:
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@@ -70,7 +69,7 @@ from transformers import AutoTokenizer
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import transformers
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import torch
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model = "
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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different industries, and advice on which qualifications would be
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beneficial for pursuing particular fields.
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- role: user
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content: Hey friend!
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- role: assistant
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content: Hi! How may I help you?
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- role: user
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- role: system
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content: You are a knowledgeable assistant. Help the user as much as you can.
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- role: user
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content: How to become smarter?
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- messages:
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- role: system
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content: You are a helpful assistant who provides concise responses.
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content: Hello there! How may I help you?
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- role: user
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content: >-
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I need to cook a simple dinner. What ingredients should I prepare for?
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- messages:
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- role: system
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content: >-
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should complete with all your knowledge.
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- role: user
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content: >-
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Write the novel story of an RPG game about group of survivor
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post apocalyptic world.
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inference:
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parameters:
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max_new_tokens: 256
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penalty_alpha: 0.5
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top_k: 4
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base_model:
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import transformers
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import torch
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model = "frankenmerger/MiniLlama-1.8b-Chat-v0.1"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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