---
base_model: Replete-AI/Replete-Coder-Qwen2-1.5b
datasets:
- Replete-AI/code_bagel_hermes-2.5
- Replete-AI/code_bagel
- Replete-AI/OpenHermes-2.5-Uncensored
- teknium/OpenHermes-2.5
- layoric/tiny-codes-alpaca
- glaiveai/glaive-code-assistant-v3
- ajibawa-2023/Code-290k-ShareGPT
- TIGER-Lab/MathInstruct
- chargoddard/commitpack-ft-instruct-rated
- iamturun/code_instructions_120k_alpaca
- ise-uiuc/Magicoder-Evol-Instruct-110K
- cognitivecomputations/dolphin-coder
- nickrosh/Evol-Instruct-Code-80k-v1
- coseal/CodeUltraFeedback_binarized
- glaiveai/glaive-function-calling-v2
- CyberNative/Code_Vulnerability_Security_DPO
- jondurbin/airoboros-2.2
- camel-ai
- lmsys/lmsys-chat-1m
- CollectiveCognition/chats-data-2023-09-22
- CoT-Alpaca-GPT4
- WizardLM/WizardLM_evol_instruct_70k
- WizardLM/WizardLM_evol_instruct_V2_196k
- teknium/GPT4-LLM-Cleaned
- GPTeacher
- OpenGPT
- meta-math/MetaMathQA
- Open-Orca/SlimOrca
- garage-bAInd/Open-Platypus
- anon8231489123/ShareGPT_Vicuna_unfiltered
- Unnatural-Instructions-GPT4
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
---
## About

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static quants of https://huggingface.co/Replete-AI/Replete-Coder-Qwen2-1.5b

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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-i1-GGUF
## Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.

## Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q2_K.gguf) | Q2_K | 0.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.IQ3_XS.gguf) | IQ3_XS | 0.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q3_K_S.gguf) | Q3_K_S | 0.9 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.IQ3_S.gguf) | IQ3_S | 0.9 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.IQ3_M.gguf) | IQ3_M | 0.9 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q3_K_M.gguf) | Q3_K_M | 0.9 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q3_K_L.gguf) | Q3_K_L | 1.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.IQ4_XS.gguf) | IQ4_XS | 1.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q4_K_S.gguf) | Q4_K_S | 1.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q5_K_S.gguf) | Q5_K_S | 1.2 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q5_K_M.gguf) | Q5_K_M | 1.2 |  |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q6_K.gguf) | Q6_K | 1.4 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.Q8_0.gguf) | Q8_0 | 1.7 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/Replete-Coder-Qwen2-1.5b-GGUF/resolve/main/Replete-Coder-Qwen2-1.5b.f16.gguf) | f16 | 3.2 | 16 bpw, overkill |

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

## FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

## Thanks

I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

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