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Model: mradermacher/next-1b-GGUF Source: Original Platform
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README.md
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---
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base_model: thelamapi/next-1b
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datasets:
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- mlabonne/FineTome-100k
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- ITCL/FineTomeOs
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- Gryphe/ChatGPT-4o-Writing-Prompts
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- dongguanting/ARPO-SFT-54K
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- GreenerPastures/All-Your-Base-Full
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- Gryphe/Opus-WritingPrompts
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- HuggingFaceH4/MATH-500
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- mlabonne/smoltalk-flat
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- mlabonne/natural_reasoning-formatted
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- OpenSPG/KAG-Thinker-training-dataset
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- uclanlp/Brief-Pro
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- CognitiveKernel/CognitiveKernel-Pro-SFT
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- SuperbEmphasis/Claude-4.0-DeepSeek-R1-RP-SFWish
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- QuixiAI/dolphin-r1
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- mlabonne/lmsys-arena-human-sft-55k
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language:
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- tr
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- ar
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- af
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- az
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- es
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- en
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- el
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- ro
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- ru
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- rm
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- th
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- uk
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- uz
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- pl
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- pt
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- fa
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- sk
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- sl
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- da
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- de
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- nl
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- fr
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- fi
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- ka
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- hi
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- hu
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- hy
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- ja
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- kk
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- kn
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- ko
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- ku
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- ky
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- la
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- lb
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- id
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- is
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- it
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- zh
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- cs
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- vi
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- be
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- bg
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- bs
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- ne
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- mn
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library_name: transformers
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license: mit
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mradermacher:
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readme_rev: 1
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quantized_by: mradermacher
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tags:
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- turkish
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- türkiye
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- english
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- ai
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- lamapi
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- gemma3
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- next
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- next-x1
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- efficient
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- text-generation
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- open-source
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- 1b
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- huggingface
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- large-language-model
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- llm
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- causal
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- transformer
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- artificial-intelligence
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- machine-learning
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- ai-research
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- natural-language-processing
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- nlp
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- finetuned
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- lightweight
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- creative
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- summarization
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- question-answering
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- chat-model
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- generative-ai
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- optimized-model
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- unsloth
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- trl
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- sft
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- chemistry
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- biology
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- finance
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- legal
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- music
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- art
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- code
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- climate
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- medical
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- agent
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- text-generation-inference
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### vocab_type: -->
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<!-- ### tags: -->
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<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
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<!-- ### quants_skip: -->
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<!-- ### skip_mmproj: -->
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static quants of https://huggingface.co/thelamapi/next-1b
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<!-- provided-files -->
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#next-1b-GGUF).***
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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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more details, including on how to concatenate multi-part files.
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## Provided Quants
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q3_K_S.gguf) | Q3_K_S | 0.8 | |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q2_K.gguf) | Q2_K | 0.8 | |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.IQ4_XS.gguf) | IQ4_XS | 0.8 | |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q3_K_M.gguf) | Q3_K_M | 0.8 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q3_K_L.gguf) | Q3_K_L | 0.9 | |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q4_K_S.gguf) | Q4_K_S | 0.9 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q4_K_M.gguf) | Q4_K_M | 0.9 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q5_K_S.gguf) | Q5_K_S | 0.9 | |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q5_K_M.gguf) | Q5_K_M | 1.0 | |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q6_K.gguf) | Q6_K | 1.1 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.Q8_0.gguf) | Q8_0 | 1.2 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/next-1b-GGUF/resolve/main/next-1b.f16.gguf) | f16 | 2.1 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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See https://huggingface.co/mradermacher/model_requests for some answers to
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questions you might have and/or if you want some other model quantized.
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## Thanks
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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me use its servers and providing upgrades to my workstation to enable
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this work in my free time.
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<!-- end -->
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size 751580448
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size 722421024
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oid sha256:18e17b2672de6e9db197b4194602c82a9df951e6c8ca673794ed3c111f18ef6c
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size 688860960
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oid sha256:158f0baabca5b4cfcea7cf7c09d03fe1ff972559f7620401242c5b6721892f02
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size 806063136
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version https://git-lfs.github.com/spec/v1
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oid sha256:5111e44db4788bea5a7201d329a9a7e00c51092518a2af0dfd1bf29860b76e29
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size 780997920
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oid sha256:4982308be9636ff0a992cef21d17a51454e0b26628e53436a2ad9d84d6b75ec2
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size 851350560
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oid sha256:b116d2e5d2c38171ccd3517172e06f8555aaaf60ba89ade718ac80ec042a2dc0
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size 836404512
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oid sha256:60551f33dd2cd23ef806d7b6a0ac9c71f44fa8e9e097e0395ccd6fb35f6ff49b
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size 1011743520
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oid sha256:e8aed9791e493e7db7e4d9d3e413a20d0c73c2ce264e3b03924b1901a67cb852
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size 1069311264
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oid sha256:d07e40a24a2e0f6678c8c23bdffe9aa6dfd6d369f68f62d17a9a20236cedf308
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size 2006578464
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