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+ ---
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+ base_model: meta-llama/Meta-Llama-3-70B-Instruct
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+ library_name: transformers
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+ tags:
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+ - axolotl
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+ - finetune
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+ - dpo
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+ - facebook
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+ - meta
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+ - pytorch
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+ - llama
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+ - llama-3
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+ - chatml
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ license: llama3
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+ license_name: llama3
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+ license_link: LICENSE
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+ inference: false
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+ model_creator: MaziyarPanahi
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+ model_name: Llama-3-70B-Instruct-DPO-v0.4
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+ quantized_by: MaziyarPanahi
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+ datasets:
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+ - Intel/orca_dpo_pairs
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+ ---
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+
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+ <img src="./llama-3-merges.webp" alt="Llama-3 DPO Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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+
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+
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+ # MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.4
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+
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+ This model is a fine-tune (DPO) of `meta-llama/Meta-Llama-3-70B-Instruct` model.
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+
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+ # Quantized GGUF
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+
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+ All GGUF models are available here: [MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.4-GGUF](https://huggingface.co/MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.4-GGUF)
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+
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+ # Prompt Template
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+
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+ This model uses `ChatML` prompt template:
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+
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+ ```
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+ <|im_start|>system
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+ {System}
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+ <|im_end|>
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+ <|im_start|>user
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+ {User}
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+ <|im_end|>
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+ <|im_start|>assistant
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+ {Assistant}
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+ ````
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+
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+ # How to use
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+
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+ You can use this model by using `MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.4` as the model name in Hugging Face's
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+ transformers library.
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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+ from transformers import pipeline
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+ import torch
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+
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+ model_id = "MaziyarPanahi/Llama-3-70B-Instruct-DPO-v0.4"
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_id,
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+ torch_dtype=torch.bfloat16,
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+ device_map="auto",
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+ trust_remote_code=True,
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+ # attn_implementation="flash_attention_2"
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+ )
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+
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+ tokenizer = AutoTokenizer.from_pretrained(
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+ model_id,
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+ trust_remote_code=True
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+ )
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+
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+ streamer = TextStreamer(tokenizer)
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+
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+ pipeline = pipeline(
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+ "text-generation",
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+ model=model,
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+ tokenizer=tokenizer,
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+ model_kwargs={"torch_dtype": torch.bfloat16},
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+ streamer=streamer
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+ )
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+
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+ # Then you can use the pipeline to generate text.
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+
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+ messages = [
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+ {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
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+ {"role": "user", "content": "Who are you?"},
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+ ]
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+
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+ prompt = tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
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+ )
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+
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+ terminators = [
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+ tokenizer.eos_token_id,
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+ tokenizer.convert_tokens_to_ids("<|im_end|>"),
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+ tokenizer.convert_tokens_to_ids("<|eot_id|>") # safer to have this too
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+ ]
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+
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+ outputs = pipeline(
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+ prompt,
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+ max_new_tokens=2048,
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+ eos_token_id=terminators,
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+ do_sample=True,
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+ temperature=0.6,
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+ top_p=0.95,
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+ )
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+ print(outputs[0]["generated_text"][len(prompt):])
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+ ```
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+
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+ ## Sample Response
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+
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+ ```
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+ <|im_start|>system
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+ You are a helpful assistant.<|im_end|>
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+ <|im_start|>user
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+ describe about pros and cons of docker system.<|im_end|>
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+ <|im_start|>assistant
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+ ```
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+
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+ ```
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+ Here are the pros and cons of the Docker system:
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+
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+ **Pros:**
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+
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+ 1. **Lightweight**: Docker containers are lightweight and use fewer resources compared to traditional virtual machines.
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+ 2. **Isolation**: Docker provides a high level of isolation between containers, ensuring that each application runs independently without interfering with others.
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+ 3. **Portability**: Docker containers are highly portable and can run on any system that supports Docker, without requiring specific dependencies or configurations.
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+ 4. **Efficient Use of Resources**: Docker containers can share the same kernel and use fewer resources, making them more efficient than traditional virtual machines.
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+ 5. **Fast Deployment**: Docker containers can be spun up quickly, making it ideal for rapid deployment and scaling of applications.
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+ 6. **Easy Maintenance**: Docker provides a simple way to manage and update applications, with features like rolling updates and rollbacks.
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+ 7. **Security**: Docker provides a secure environment for applications, with features like network isolation and encryption.
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+ 8. **Large Ecosystem**: Docker has a large and active ecosystem, with a wide range of tools and plugins available for various tasks.
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+ 9. **Version Control**: Docker provides an easy way to manage different versions of an application, with features like version tagging and rollbacks.
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+ 10. **Cost-Effective**: Docker can help reduce costs by minimizing the need for virtual machines and reducing the overhead of resource allocation.
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+
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+ **Cons:**
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+
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+ 1. **Steep Learning Curve**: Docker has a complex architecture and requires a good understanding of containerization, networking, and storage.
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+ 2. **Overhead**: While Docker containers are lightweight, they still require some overhead in terms of resources and management.
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+ 3. **Security Risks**: If not properly configured, Docker containers can introduce security risks, such as unauthorized access to the host system.
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+ 4. **Limited Support for GUI Applications**: Docker is primarily designed for running command-line applications, and running GUI applications can be challenging.
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+ 5. **Networking Complexity**: Docker's networking model can be complex, especially in large-scale deployments.
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+ 6. **Storage Complexity**: Docker's storage model can be complex, especially when dealing with persistent data.
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+ 7. **Limited Support for Legacy Applications**: Docker is designed for modern, cloud-native applications, and may not be suitable for legacy applications that rely on older technologies.
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+ 8. **Dependence on Docker Hub**: Docker relies heavily on Docker Hub, which can be a single point of failure if the hub is down or experiencing issues.
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+ 9. **Orchestration Complexity**: Docker provides a built-in orchestration tool, Docker Swarm, but it can be complex to set up and manage.
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+ 10. **Vendor Lock-in**: Docker is a proprietary technology, and while it has a large ecosystem, it can be difficult to switch to alternative containerization platforms.
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+
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+ Overall, Docker provides a powerful and flexible way to deploy and manage applications, but it requires careful planning, configuration, and management to ensure optimal performance and security.
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+ ```