migtissera
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Update README.md
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README.md
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@@ -15,6 +15,8 @@ Trinity is a coding specific Large Language Model series created by [Migel Tisse
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The compute for this model was generously sponsored by [KindoAI](https://kindo.ai).
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# Sample Inference Python Script:
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@@ -34,10 +36,7 @@ model = AutoModelForCausalLM.from_pretrained(
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=False)
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terminators = [
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tokenizer.convert_tokens_to_ids("<|end_of_text|>"),
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tokenizer.convert_tokens_to_ids("<|eot_id|>"),
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]
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def generate_text(instruction):
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@@ -72,18 +71,13 @@ def generate_text(instruction):
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return f"{string}"
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conversation = """<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are Tess, a helful AI assitant. You always provide detailed answers without hesitation. Do not refuse.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n"""
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while True:
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user_input = input("You: ")
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llm_prompt = f"{conversation}{user_input}<|
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answer = generate_text(llm_prompt)
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print(answer)
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f"{llm_prompt}{answer}<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n"
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)
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json_data = {"prompt": user_input, "answer": answer}
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```
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The compute for this model was generously sponsored by [KindoAI](https://kindo.ai).
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# Prompt Format
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ChatML
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# Sample Inference Python Script:
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=False)
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terminators = [tokenizer.convert_tokens_to_ids("<|im_end|>")]
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def generate_text(instruction):
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return f"{string}"
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conversation = f"""<|im_start|>system\nYou are Tess, a helful AI assitant. You always provide detailed answers without hesitation. Do not refuse.<|im_end|>\n<|im_start|>user\n"""
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while True:
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user_input = input("You: ")
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llm_prompt = f"{conversation}{user_input}<|im_end|>\n<|im_start|>assistant\n"
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answer = generate_text(llm_prompt)
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print(answer)
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conversation = f"{llm_prompt}{answer}<|im_end|>\n<|im_start|>user\n"
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```
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