Zephyr Quiklang 3B GGUF by TheBloke

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Base model:quantized:walmart-t... Base model:walmart-the-bag/zep...   Causal lm   Conversational   Dataset:teknium/openhermes Dataset:unalignment/toxic-dpo-...   Gguf   Quantized   Region:us   Stablelm epoch

Zephyr Quiklang 3B GGUF Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Zephyr Quiklang 3B GGUF (TheBloke/zephyr-quiklang-3b-GGUF)

Zephyr Quiklang 3B GGUF Parameters and Internals

Model Type 
stablelm_epoch
Additional Notes 
This model was quantised using GGUF format.
Training Details 
Data Sources:
unalignment/toxic-dpo-v0.1, teknium/openhermes
Data Volume:
10000 samples
Context Length:
1024
Hardware Used:
1xA6000-48GB
Input Output 
Input Format:
<|system|> {system_message}~~ <|user|> {prompt}~~ <|assistant|>
LLM NameZephyr Quiklang 3B GGUF
Repository ๐Ÿค—https://huggingface.co/TheBloke/zephyr-quiklang-3b-GGUF 
Model NameZephyr Quiklang 3B
Model Creatorwbag
Base Model(s)  Zephyr Quiklang 3B   Walmart-the-bag/zephyr-quiklang-3b
Model Size3b
Required VRAM1.2 GB
Updated2025-02-05
MaintainerTheBloke
Model Typestablelm_epoch
Model Files  1.2 GB   1.5 GB   1.4 GB   1.2 GB   1.6 GB   1.7 GB   1.6 GB   1.9 GB   2.0 GB   1.9 GB   2.3 GB   3.0 GB
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licensemit

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/zephyr-quiklang-3b-GGUF.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227