---
language:
- tr
- en
license: apache-2.0
datasets:
- malhajar/meditron-tr
base_model: malhajar/Mistral-7B-v0.2-meditron-turkish
tags:
- TensorBlock
- GGUF
model-index:
- name: Mistral-7B-v0.2-meditron-turkish
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 59.56
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 81.79
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 60.35
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 66.19
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 76.24
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 35.94
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
name: Open LLM Leaderboard
---
## malhajar/Mistral-7B-v0.2-meditron-turkish - GGUF
This repo contains GGUF format model files for [malhajar/Mistral-7B-v0.2-meditron-turkish](https://huggingface.co/malhajar/Mistral-7B-v0.2-meditron-turkish).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
## Prompt template
```
[INST] {prompt} [/INST]
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Mistral-7B-v0.2-meditron-turkish-Q2_K.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q2_K.gguf) | Q2_K | 2.532 GB | smallest, significant quality loss - not recommended for most purposes |
| [Mistral-7B-v0.2-meditron-turkish-Q3_K_S.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q3_K_S.gguf) | Q3_K_S | 2.947 GB | very small, high quality loss |
| [Mistral-7B-v0.2-meditron-turkish-Q3_K_M.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q3_K_M.gguf) | Q3_K_M | 3.277 GB | very small, high quality loss |
| [Mistral-7B-v0.2-meditron-turkish-Q3_K_L.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q3_K_L.gguf) | Q3_K_L | 3.560 GB | small, substantial quality loss |
| [Mistral-7B-v0.2-meditron-turkish-Q4_0.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q4_0.gguf) | Q4_0 | 3.827 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Mistral-7B-v0.2-meditron-turkish-Q4_K_S.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q4_K_S.gguf) | Q4_K_S | 3.856 GB | small, greater quality loss |
| [Mistral-7B-v0.2-meditron-turkish-Q4_K_M.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q4_K_M.gguf) | Q4_K_M | 4.068 GB | medium, balanced quality - recommended |
| [Mistral-7B-v0.2-meditron-turkish-Q5_0.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q5_0.gguf) | Q5_0 | 4.654 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Mistral-7B-v0.2-meditron-turkish-Q5_K_S.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q5_K_S.gguf) | Q5_K_S | 4.654 GB | large, low quality loss - recommended |
| [Mistral-7B-v0.2-meditron-turkish-Q5_K_M.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q5_K_M.gguf) | Q5_K_M | 4.779 GB | large, very low quality loss - recommended |
| [Mistral-7B-v0.2-meditron-turkish-Q6_K.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q6_K.gguf) | Q6_K | 5.534 GB | very large, extremely low quality loss |
| [Mistral-7B-v0.2-meditron-turkish-Q8_0.gguf](https://huggingface.co/tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF/blob/main/Mistral-7B-v0.2-meditron-turkish-Q8_0.gguf) | Q8_0 | 7.167 GB | very large, extremely low quality loss - not recommended |
## Downloading instruction
### Command line
Firstly, install Huggingface Client
```shell
pip install -U "huggingface_hub[cli]"
```
Then, downoad the individual model file the a local directory
```shell
huggingface-cli download tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF --include "Mistral-7B-v0.2-meditron-turkish-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
```shell
huggingface-cli download tensorblock/Mistral-7B-v0.2-meditron-turkish-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```