Praudyog

Category: Generative AI

  • GenAI – Open Source LLM Models.

    GenAI – Open Sourced LLM Models. Table Of Contents: What Is Open Source LLM Models ? Characteristics Of Open Source LLM. When To Use Open Source LLM. Advantages Of Open Source LLM Models. Dis Advantages Of Open Source LLM Models. List Of Open Source LLM Models. (1) What Is Open Source LLM Models ? (2) Characteristics Of Open Source LLM Models . (3) When To Use Open Source LLM Models ? (4) When Not To Use Open Source LLM Models ? (5) Advantages Of Open Source LLM Models ? (6) Disadvantages Of Open Source LLM Models ? (7) List Of

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  • GenAI – Close Source LLM Models.

    GenAI – Close Sourced LLM Models. Table Of Contents: What Is Close Source LLM Models ? Characteristics Of Close Source LLM. When To Use Close Source LLM. When Not To Use Close Source LLM. Advantages Of Close Source LLM Models. Dis Advantages Of Close Source LLM Models. List Of Close Source LLM Models. (1) What Is Close Source LLM Models ? (2) Characteristics Of Close Source LLM Models . (3) When To Use Close Source LLM ? (4) When Not To Use Close Source LLM ? (5) Advantages Of Close Source LLM. (6) Disadvantages Of Close Source LLM. (7) List

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  • GenAI – Evaluation Metrics In LLM.

    GenAI – Evaluation Metrics In LLM.

    GenAI – LLM Model Evaluation Metrics. Table Of Contents: Automatic Evaluation Metrics. Human Evaluation (Gold Standard). Hallucination Detection. Embedding/Similarity Based. Application-Specific Evaluation. Evaluation Frameworks. (1) Automatic Evaluation Metrics (2) Human Evaluation (Gold Standard). (3) Hallucination Detection (4) Embedding/Similarity Based (5) Application-Specific Evaluation (6) Evaluation Frameworks

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  • GenAI – BitFit Tuning.

  • GenAI – Instruction Tuning.

    GenAI – Instruction Tuning. Table Of Contents: What Is Instruction Tuning? Steps Involved In Instruction Tuning. Example Of Instruction Tuning. Instruction Tuning Vs Few Shot Prompting. (1) What Is Instruction Tuning ? (2) How Instruction Tuning Helps ? (2) Steps Involved In Instruction Tuning . (2) Example Of Instruction Tuning ? Step-1: Install Required Libraries pip install transformers datasets peft accelerate bitsandbytes Step-2: Sample Instruction Dataset We’ll use a few inline samples. In real cases, use a larger dataset like Alpaca, FLAN, or Self-Instruct. from datasets import Dataset # Sample toy dataset with instruction-style tasks data = [ { "instruction":

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  • GenAI – Prompt Tuning .

  • GenAI – Prefix Tuning .

  • GenAI – IA³ Adapters Tuning .

  • GenAI – Bottleneck Adapters Tuning .

    GenAI – Bottleneck Adapters Tuning .

  • GenAI – What Is Hugging Face PEFT ?

    GenAI – What Is Hugging Face PEFT ?

    GenAI – What Is Hugging Face PEFT ? Table Of Contents: What Is Hugging Face PEFT ? What Is PEFT ? Features of Hugging Face PEFT . Example: Using LoRA via Hugging Face PEFT Supported Techniques in PEFT Library (1) What Is Hugging Face PEFT ? (2) What Is PEFT ? (3) Features Of Hugging Face PEFT . (4) Example: Using LoRA via Hugging Face PEFT from transformers import AutoModelForCausalLM, AutoTokenizer from peft import get_peft_model, LoraConfig, TaskType model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-hf") # Define LoRA configuration lora_config = LoraConfig( r=8, lora_alpha=16, target_modules=["q_proj", "v_proj"], lora_dropout=0.05, task_type=TaskType.CAUSAL_LM ) # Apply PEFT

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