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+ ---
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+ base_model: Felladrin/Llama-160M-Chat-v1
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+ datasets:
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+ - ehartford/wizard_vicuna_70k_unfiltered
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+ - totally-not-an-llm/EverythingLM-data-V3
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+ - Open-Orca/SlimOrca-Dedup
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+ - databricks/databricks-dolly-15k
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+ - THUDM/webglm-qa
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+ inference: false
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+ license: other
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+ model_creator: Felladrin
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+ model_name: Llama-160M-Chat-v1
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+ pipeline_tag: text-generation
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+ quantized_by: afrideva
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+ tags:
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+ - text-generation
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+ - gguf
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+ - ggml
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+ - quantized
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+ - q2_k
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+ - q3_k_m
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+ - q4_k_m
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+ - q5_k_m
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+ - q6_k
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+ - q8_0
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+ widget:
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+ - text: "<|im_start|>system\nYou are a helpful assistant, who answers with empathy.<|im_end|>\n<|im_start|>user\nGot
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+ a question for you!<|im_end|>\n<|im_start|>assistant\nSure! What's it?<|im_end|>\n<|im_start|>user\nWhy
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+ do you love cats so much!? \U0001F408<|im_end|>\n<|im_start|>assistant"
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+ - text: '<|im_start|>system
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+
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+ You are a helpful assistant who answers user''s questions with empathy.<|im_end|>
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+
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+ <|im_start|>user
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+
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+ Who is Mona Lisa?<|im_end|>
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+
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+ <|im_start|>assistant'
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+ - text: '<|im_start|>system
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+
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+ You are a helpful assistant who provides concise responses.<|im_end|>
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+
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+ <|im_start|>user
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+
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+ Heya!<|im_end|>
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+
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+ <|im_start|>assistant
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+
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+ Hi! How may I help you today?<|im_end|>
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+
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+ <|im_start|>user
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+
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+ I need to build a simple website. Where should I start learning about web development?<|im_end|>
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+
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+ <|im_start|>assistant'
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+ - text: '<|im_start|>user
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+
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+ Invited some friends to come home today. Give me some ideas for games to play
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+ with them!<|im_end|>
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+
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+ <|im_start|>assistant'
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+ - text: '<|im_start|>system
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+
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+ You are a helpful assistant who answers user''s questions with details and curiosity.<|im_end|>
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+
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+ <|im_start|>user
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+
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+ What are some potential applications for quantum computing?<|im_end|>
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+
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+ <|im_start|>assistant'
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+ - text: '<|im_start|>system
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+
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+ You are a helpful assistant who gives creative responses.<|im_end|>
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+
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+ <|im_start|>user
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+
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+ Write the specs of a game about mages in a fantasy world.<|im_end|>
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+
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+ <|im_start|>assistant'
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+ - text: '<|im_start|>system
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+
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+ You are a helpful assistant who answers user''s questions with details.<|im_end|>
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+
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+ <|im_start|>user
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+
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+ Tell me about the pros and cons of social media.<|im_end|>
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+
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+ <|im_start|>assistant'
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+ - text: '<|im_start|>system
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+
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+ You are a helpful assistant who answers user''s questions with confidence.<|im_end|>
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+
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+ <|im_start|>user
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+
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+ What is a dog?<|im_end|>
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+
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+ <|im_start|>assistant
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+
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+ A dog is a four-legged, domesticated animal that is a member of the class Mammalia,
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+ which includes all mammals. Dogs are known for their loyalty, playfulness, and
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+ ability to be trained for various tasks. They are also used for hunting, herding,
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+ and as service animals.<|im_end|>
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+
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+ <|im_start|>user
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+
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+ What is the color of an apple?<|im_end|>
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+
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+ <|im_start|>assistant'
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+ ---
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+ # Felladrin/Llama-160M-Chat-v1-GGUF
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+
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+ Quantized GGUF model files for [Llama-160M-Chat-v1](https://huggingface.co/Felladrin/Llama-160M-Chat-v1) from [Felladrin](https://huggingface.co/Felladrin)
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+
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+
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+ | Name | Quant method | Size |
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+ | ---- | ---- | ---- |
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+ | [llama-160m-chat-v1.fp16.gguf](https://huggingface.co/afrideva/Llama-160M-Chat-v1-GGUF/resolve/main/llama-160m-chat-v1.fp16.gguf) | fp16 | 326.58 MB |
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+ | [llama-160m-chat-v1.q2_k.gguf](https://huggingface.co/afrideva/Llama-160M-Chat-v1-GGUF/resolve/main/llama-160m-chat-v1.q2_k.gguf) | q2_k | 77.23 MB |
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+ | [llama-160m-chat-v1.q3_k_m.gguf](https://huggingface.co/afrideva/Llama-160M-Chat-v1-GGUF/resolve/main/llama-160m-chat-v1.q3_k_m.gguf) | q3_k_m | 87.54 MB |
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+ | [llama-160m-chat-v1.q4_k_m.gguf](https://huggingface.co/afrideva/Llama-160M-Chat-v1-GGUF/resolve/main/llama-160m-chat-v1.q4_k_m.gguf) | q4_k_m | 104.03 MB |
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+ | [llama-160m-chat-v1.q5_k_m.gguf](https://huggingface.co/afrideva/Llama-160M-Chat-v1-GGUF/resolve/main/llama-160m-chat-v1.q5_k_m.gguf) | q5_k_m | 119.04 MB |
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+ | [llama-160m-chat-v1.q6_k.gguf](https://huggingface.co/afrideva/Llama-160M-Chat-v1-GGUF/resolve/main/llama-160m-chat-v1.q6_k.gguf) | q6_k | 135.00 MB |
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+ | [llama-160m-chat-v1.q8_0.gguf](https://huggingface.co/afrideva/Llama-160M-Chat-v1-GGUF/resolve/main/llama-160m-chat-v1.q8_0.gguf) | q8_0 | 174.33 MB |
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+
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+
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+
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+ ## Original Model Card:
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+ # A Llama Chat Model of 160M Parameters
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+
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+ - Base model: [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m)
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+ - Datasets:
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+ - [ehartford/wizard_vicuna_70k_unfiltered](https://huggingface.co/datasets/ehartford/wizard_vicuna_70k_unfiltered)
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+ - [totally-not-an-llm/EverythingLM-data-V3](https://huggingface.co/datasets/totally-not-an-llm/EverythingLM-data-V3)
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+ - [Open-Orca/SlimOrca-Dedup](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup)
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+ - [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)
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+ - [THUDM/webglm-qa](https://huggingface.co/datasets/THUDM/webglm-qa)
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+ - Availability in other ML formats:
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+ - GGUF: [Felladrin/gguf-Llama-160M-Chat-v1](https://huggingface.co/Felladrin/gguf-Llama-160M-Chat-v1)
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+ - ONNX: [Felladrin/onnx-Llama-160M-Chat-v1](https://huggingface.co/Felladrin/onnx-Llama-160M-Chat-v1)
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+
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+ ## Recommended Prompt Format
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+
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+ The recommended prompt format is as follows:
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+
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+ ```
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+ <|im_start|>system
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+ {system_message}<|im_end|>
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+ <|im_start|>user
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+ {user_message}<|im_end|>
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+ <|im_start|>assistant
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+ ```
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+
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+ ## Recommended Inference Parameters
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+
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+ To get the best results, prefer using [contrastive search](https://huggingface.co/docs/transformers/main/en/generation_strategies#contrastive-search) for inference:
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+
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+ ```yml
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+ penalty_alpha: 0.5
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+ top_k: 5
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+ ```