---
language:
- en
license: other
tags:
- TensorBlock
- GGUF
base_model: Nitral-AI/Hathor_Stable-v0.2-L3-8B
model-index:
- name: Hathor_Stable-v0.2-L3-8B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 71.75
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nitral-AI/Hathor_Stable-v0.2-L3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 32.83
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nitral-AI/Hathor_Stable-v0.2-L3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 9.21
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nitral-AI/Hathor_Stable-v0.2-L3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 4.92
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nitral-AI/Hathor_Stable-v0.2-L3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 5.56
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nitral-AI/Hathor_Stable-v0.2-L3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 29.96
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Nitral-AI/Hathor_Stable-v0.2-L3-8B
name: Open LLM Leaderboard
---
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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## Nitral-AI/Hathor_Stable-v0.2-L3-8B - GGUF
This repo contains GGUF format model files for [Nitral-AI/Hathor_Stable-v0.2-L3-8B](https://huggingface.co/Nitral-AI/Hathor_Stable-v0.2-L3-8B).
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).
<div style="text-align: left; margin: 20px 0;">
<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
Run them on the TensorBlock client using your local machine ↗
</a>
</div>
## Prompt template
```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Hathor_Stable-v0.2-L3-8B-Q2_K.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q2_K.gguf) | Q2_K | 3.179 GB | smallest, significant quality loss - not recommended for most purposes |
| [Hathor_Stable-v0.2-L3-8B-Q3_K_S.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q3_K_S.gguf) | Q3_K_S | 3.664 GB | very small, high quality loss |
| [Hathor_Stable-v0.2-L3-8B-Q3_K_M.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q3_K_M.gguf) | Q3_K_M | 4.019 GB | very small, high quality loss |
| [Hathor_Stable-v0.2-L3-8B-Q3_K_L.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q3_K_L.gguf) | Q3_K_L | 4.322 GB | small, substantial quality loss |
| [Hathor_Stable-v0.2-L3-8B-Q4_0.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q4_0.gguf) | Q4_0 | 4.661 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Hathor_Stable-v0.2-L3-8B-Q4_K_S.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q4_K_S.gguf) | Q4_K_S | 4.693 GB | small, greater quality loss |
| [Hathor_Stable-v0.2-L3-8B-Q4_K_M.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q4_K_M.gguf) | Q4_K_M | 4.921 GB | medium, balanced quality - recommended |
| [Hathor_Stable-v0.2-L3-8B-Q5_0.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q5_0.gguf) | Q5_0 | 5.599 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Hathor_Stable-v0.2-L3-8B-Q5_K_S.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q5_K_S.gguf) | Q5_K_S | 5.599 GB | large, low quality loss - recommended |
| [Hathor_Stable-v0.2-L3-8B-Q5_K_M.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q5_K_M.gguf) | Q5_K_M | 5.733 GB | large, very low quality loss - recommended |
| [Hathor_Stable-v0.2-L3-8B-Q6_K.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q6_K.gguf) | Q6_K | 6.596 GB | very large, extremely low quality loss |
| [Hathor_Stable-v0.2-L3-8B-Q8_0.gguf](https://huggingface.co/tensorblock/Hathor_Stable-v0.2-L3-8B-GGUF/blob/main/Hathor_Stable-v0.2-L3-8B-Q8_0.gguf) | Q8_0 | 8.541 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/Hathor_Stable-v0.2-L3-8B-GGUF --include "Hathor_Stable-v0.2-L3-8B-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/Hathor_Stable-v0.2-L3-8B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```