🐬 Dolphin-2.9-llama3-8b 🐬 TESTED: Llama3 Finetunes are already Incredible!
TLDRThe video discusses the advancements in AI language models, highlighting the recent developments with Meta's Llama 3 model, which has surpassed Mistral 8 x7b as the new standard for fine-tuning and modification. The focus is on Eric Hartford's Dolphin 2.9 Llama 3-8b, an 8 billion parameter model that showcases impressive capabilities, including instruction tuning and enhanced problem-solving skills. The model has been fine-tuned using a curated dataset and has demonstrated a more concise and directive approach to queries. It also supports function calling, an important feature for agentic abilities. The video explores the model's performance through various prompts, emphasizing its uncensored nature and its potential for practical use in an agentic workflow. The host also touches on the importance of responsible implementation and the need for caution when deploying such models.
Takeaways
- 🐬 Meta's Llama 3 model is surpassing Mistral 8x7b as the new standard for fine-tuning and modification in AI research.
- 📈 Llama 3, even in its current form, is considered state-of-the-art, with capabilities that researchers are actively exploring and adopting.
- 📱 Recent advancements have enabled Llama 3 to run on various platforms, including Apple Silicon and even iPhones.
- 🔍 Eric Hartford's first release focused on Llama 3 is noted for its uncensored nature and strong performance, although it's not the leading 8 billion parameter model.
- 🤖 Dolphin 2.9 Llama 38b, released by Eric, is an 8 billion parameter model with enhanced data sets and initial agentic abilities.
- 🚀 The model is trained with an instructive ChatML prompting format, which makes it more directive and capable of function calling.
- 📚 Training data for Dolphin 2.9 includes Hugging Face H4, Open Hermes, and Microsoft Orca math word problems, focusing on real-world problem-solving and reasoning.
- 🔨 Dolphin 2.9 has been filtered to remove certain biases, making it more compliant and understanding of user prompts.
- 🚫 Despite being uncensored, the model provides metered and cautious responses, emphasizing safety and professional assessment when needed.
- 📝 The model demonstrates an ability to give concise and nuanced responses, understanding when to stop and not overextend its answers.
- 🌊 In a nautical example, the model suggests hiding items in lockable, less accessible compartments on a boat, showing its understanding of context and user intent.
Q & A
Which AI model has recently been considered the new standard for fine-tuning and modification?
-Meta's Llama 3 model has been considered the new standard for fine-tuning and modification, dethroning Mistil 8 x7b.
What is the significance of the Llama 3 model's release in terms of AI development?
-The Llama 3 model's release signifies a sea change in AI development, as it introduces a new state-of-the-art model that is more capable and uncensored, leading to a shift in focus for researchers towards fine-tuning and modifying Llama 3.
How does the Dolphin 2.9 Llama 3 model compare to the base Llama 3 model?
-The Dolphin 2.9 Llama 3 model is more uncensored than the base model and has a similar relative performance. It also has enhanced data set focus and initial agentic abilities.
What are the key features of the Dolphin 2.9 Llama 3 model that make it stand out?
-The Dolphin 2.9 Llama 3 model has a variety of instruction, conversational, and coding skills, supports function calling, and has been filtered to remove certain alignment biases, making it more compliant and understanding.
What is the training process for the Dolphin 2.9 Llama 3 model?
-The model was trained using an 8K context length with a 4K sequence length, taking about 2 and a half days on eight Nvidia L4s GPUs, and was trained using FFT on all parameters.
What kind of data sets were used to train the Dolphin 2.9 Llama 3 model?
-The training data sets included Hugging Face H4, UltraT 200k, Open Hermes 22.5 from Noesis Research, and Microsoft Orca Math Word Problems 200k, which focus on chat data, instruction tuning, real-world problem solving, and reasoning.
How does the Dolphin 2.9 Llama 3 model handle vague prompts?
-The model handles vague prompts by being more incisive, to the point, and concise, which is an improvement over the stock Llama 3 model.
What is the importance of using the CHATML template with the Dolphin 2.9 Llama 3 model?
-The CHATML template makes the model more directive, enhancing its ability to understand and respond to prompts effectively, and is considered a force multiplier when fine-tuning with templates.
How does the model respond to a prompt about fixing a leak in a sailboat?
-The model provides a nuanced response, suggesting checking seals and hoses for damage and using a patch or sealant if a leak is found, and advises caution by consulting a professional if the source of the leak is not identifiable.
What is the model's stance on providing suggestions for hiding items in a boat?
-The model suggests hiding items in a lockable storage compartment that is not easily accessible from the main living area, such as below decks or inside a large piece of furniture or equipment, and to secure it with a sturdy padlock or latch.
What is the general feedback on the Dolphin 2.9 Llama 3 model's performance?
-The model is impressive for its ability to provide concise and metered responses without overrunning, showing an understanding of the context and the ability to constrain its output effectively.
Outlines
📉 Shift to Llama 3: The New AI Standard
The first paragraph discusses the recent shift in the AI research community from the previously dominant Mistal 8 x7b model to Meta's Llama 3 model. Despite not having the most powerful version yet, Llama 3 is already setting the new standard for fine-tuning and modification to create more powerful AI implementations. The paragraph also highlights the capabilities of Eric Hartford's first release focused on Llama 3, which is uncensored and shows relative performance similar to Llama 3, but isn't necessarily the leading model. The discussion also touches on the importance of benchmarking these models and the potential of Llama 3's structure to influence future models, including Meta's upcoming 400b plus model.
🚀 Llama 3's Impact and Training Insights
The second paragraph delves into the impact of Llama 3 and the training datasets used to enhance its capabilities. It mentions the use of Hugging Face H4, UltraT 200k, Open Hermes 22.5, and Microsoft Orca Math Word Problems 200k datasets to improve the model's reasoning and problem-solving skills. The paragraph also provides an example of how the model responds to a prompt about fixing a leak in a sailboat, demonstrating its ability to provide nuanced and cautious advice without overstepping ethical boundaries.
🔍 Navigating Uncensored AI and Practical Applications
The third paragraph explores the uncensored nature of the Llama 3 model and its practical applications. It discusses the model's ability to provide concise and contextually aware responses without needing excessive prompting. The paragraph also presents a scenario where the model is asked about hiding items in a sailboat, to which it responds with a safe and practical suggestion. The speaker expresses their intention to continue testing the model and possibly start live streams to share their findings, inviting viewer feedback and engagement.
Mindmap
Keywords
💡Llama 3
💡Fine-tuning
💡Dolphin 2.9
💡Instruction Tuning
💡Agentic Abilities
💡Function Calling
💡Hugging Face
💡Open Chat ML
💡Bias and Alignment
💡NVIDIA L4s GPUs
💡Uncensored
Highlights
Meta's Llama 3 model has surpassed Mistal 8 x7b in terms of capabilities.
Llama 3 is becoming the new standard for fine-tuning and modification in AI research.
Dolphin 2.9 Llama 38b is an 8 billion parameter model with enhanced capabilities and is uncensored.
The model's performance is similar to Llama 3, but it is not necessarily the leading 8 billion parameter model.
Eric Hartford's release of Dolphin 2.9 Llama 38b focuses on instruction tuning and problem-solving.
The model uses an enhanced dataset and has initial agentic abilities, supporting function calling.
Dolphin 2.9 is more uncensored than the base Llama 3 model, providing a more compliant response to prompts.
The model still uses the old chat EML format, but an update to Open Chat ML is expected soon.
Training for Dolphin 2.9 Llama 38b took 2.5 days on eight Nvidia L4s GPUs.
The model incorporates a variety of skills, including conversational and coding abilities.
Dolphin 2.9 has been filtered to remove certain alignment biases, improving compliance and understanding.
The model is capable of providing nuanced and metered responses, even when given vague prompts.
Dolphin 2.9 demonstrates an understanding of context and can provide directed problem-solving steps.
The model is concise and does not overrun its output, showing an ability to provide meaningful responses within token limits.
Using the CHAT template with Dolphin 2.9 enhances the model's performance and provides a force multiplier effect.
Dolphin 2.9's uncensored nature allows for more direct and potentially sensitive responses when prompted.
The model's training included datasets like Hugging Face H4, Open Hermes, and Microsoft Orca Math Word Problems.
Dolphin 2.9 is licensed under Meta's Llama license, allowing for its use in various applications.
The model's performance is evaluated against human-centric benchmarks provided by Meta.
The video suggests that live streams or videos showcasing the model's capabilities may be upcoming.