---
license: other
tags:
- axolotl
- generated_from_trainer
- Mistral
- instruct
- finetune
- chatml
- gpt4
- synthetic data
- science
- physics
- chemistry
- biology
- math
base_model: alpindale/Mistral-7B-v0.2-hf
datasets:
- allenai/ai2_arc
- camel-ai/physics
- camel-ai/chemistry
- camel-ai/biology
- camel-ai/math
- metaeval/reclor
- openbookqa
- mandyyyyii/scibench
- derek-thomas/ScienceQA
- TIGER-Lab/ScienceEval
- jondurbin/airoboros-3.2
- LDJnr/Capybara
- Cot-Alpaca-GPT4-From-OpenHermes-2.5
- STEM-AI-mtl/Electrical-engineering
- knowrohit07/saraswati-stem
- sablo/oasst2_curated
- lmsys/lmsys-chat-1m
- TIGER-Lab/MathInstruct
- bigbio/med_qa
- meta-math/MetaMathQA-40K
- openbookqa
- piqa
- metaeval/reclor
- derek-thomas/ScienceQA
- scibench
- sciq
- Open-Orca/SlimOrca
- migtissera/Synthia-v1.3
- TIGER-Lab/ScienceEval
- allenai/WildChat
- microsoft/orca-math-word-problems-200k
- openchat/openchat_sharegpt4_dataset
- teknium/GPTeacher-General-Instruct
- m-a-p/CodeFeedback-Filtered-Instruction
quantized_by: bartowski
pipeline_tag: text-generation
---

## Llamacpp Quantizations of Einstein-v5-v0.2-7B

Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2536">b2536</a> for quantization.

Original model: https://huggingface.co/Weyaxi/Einstein-v5-v0.2-7B

Download a file (not the whole branch) from below:

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Einstein-v5-v0.2-7B-Q8_0.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q8_0.gguf) | Q8_0 | 7.69GB | Extremely high quality, generally unneeded but max available quant. |
| [Einstein-v5-v0.2-7B-Q6_K.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q6_K.gguf) | Q6_K | 5.94GB | Very high quality, near perfect, *recommended*. |
| [Einstein-v5-v0.2-7B-Q5_K_M.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q5_K_M.gguf) | Q5_K_M | 5.13GB | High quality, very usable. |
| [Einstein-v5-v0.2-7B-Q5_K_S.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q5_K_S.gguf) | Q5_K_S | 4.99GB | High quality, very usable. |
| [Einstein-v5-v0.2-7B-Q5_0.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q5_0.gguf) | Q5_0 | 4.99GB | High quality, older format, generally not recommended. |
| [Einstein-v5-v0.2-7B-Q4_K_M.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q4_K_M.gguf) | Q4_K_M | 4.36GB | Good quality, uses about 4.83 bits per weight. |
| [Einstein-v5-v0.2-7B-Q4_K_S.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q4_K_S.gguf) | Q4_K_S | 4.14GB | Slightly lower quality with small space savings. |
| [Einstein-v5-v0.2-7B-IQ4_NL.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-IQ4_NL.gguf) | IQ4_NL | 4.15GB | Decent quality, similar to Q4_K_S, new method of quanting, |
| [Einstein-v5-v0.2-7B-IQ4_XS.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-IQ4_XS.gguf) | IQ4_XS | 3.94GB | Decent quality, new method with similar performance to Q4. |
| [Einstein-v5-v0.2-7B-Q4_0.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q4_0.gguf) | Q4_0 | 4.10GB | Decent quality, older format, generally not recommended. |
| [Einstein-v5-v0.2-7B-Q3_K_L.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q3_K_L.gguf) | Q3_K_L | 3.82GB | Lower quality but usable, good for low RAM availability. |
| [Einstein-v5-v0.2-7B-Q3_K_M.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q3_K_M.gguf) | Q3_K_M | 3.51GB | Even lower quality. |
| [Einstein-v5-v0.2-7B-IQ3_M.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-IQ3_M.gguf) | IQ3_M | 3.28GB | Medium-low quality, new method with decent performance. |
| [Einstein-v5-v0.2-7B-IQ3_S.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-IQ3_S.gguf) | IQ3_S | 3.18GB | Lower quality, new method with decent performance, recommended over Q3 quants. |
| [Einstein-v5-v0.2-7B-Q3_K_S.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q3_K_S.gguf) | Q3_K_S | 3.16GB | Low quality, not recommended. |
| [Einstein-v5-v0.2-7B-Q2_K.gguf](https://huggingface.co/bartowski/Einstein-v5-v0.2-7B-GGUF/blob/main/Einstein-v5-v0.2-7B-Q2_K.gguf) | Q2_K | 2.71GB | Extremely low quality, *not* recommended.

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