File size: 6,490 Bytes

---
license: agpl-3.0
language:
- zh
tags:
- PULSE
- llm
- TensorBlock
- GGUF
base_model: OpenMEDLab/PULSE-7bv5
---

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## OpenMEDLab/PULSE-7bv5 - GGUF

This repo contains GGUF format model files for [OpenMEDLab/PULSE-7bv5](https://huggingface.co/OpenMEDLab/PULSE-7bv5).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5165](https://github.com/ggml-org/llama.cpp/commit/1d735c0b4fa0551c51c2f4ac888dd9a01f447985).

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## Prompt template

```
Instructions: You are Helper, a large language model full of intelligence. Respond conversationally.</s>User: {prompt}</s>Helper: 
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [PULSE-7bv5-Q2_K.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q2_K.gguf) | Q2_K | 3.437 GB | smallest, significant quality loss - not recommended for most purposes |
| [PULSE-7bv5-Q3_K_S.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q3_K_S.gguf) | Q3_K_S | 3.899 GB | very small, high quality loss |
| [PULSE-7bv5-Q3_K_M.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q3_K_M.gguf) | Q3_K_M | 4.442 GB | very small, high quality loss |
| [PULSE-7bv5-Q3_K_L.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q3_K_L.gguf) | Q3_K_L | 4.748 GB | small, substantial quality loss |
| [PULSE-7bv5-Q4_0.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q4_0.gguf) | Q4_0 | 4.837 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [PULSE-7bv5-Q4_K_S.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q4_K_S.gguf) | Q4_K_S | 4.863 GB | small, greater quality loss |
| [PULSE-7bv5-Q4_K_M.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q4_K_M.gguf) | Q4_K_M | 5.268 GB | medium, balanced quality - recommended |
| [PULSE-7bv5-Q5_0.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q5_0.gguf) | Q5_0 | 5.721 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [PULSE-7bv5-Q5_K_S.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q5_K_S.gguf) | Q5_K_S | 5.721 GB | large, low quality loss - recommended |
| [PULSE-7bv5-Q5_K_M.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q5_K_M.gguf) | Q5_K_M | 6.046 GB | large, very low quality loss - recommended |
| [PULSE-7bv5-Q6_K.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q6_K.gguf) | Q6_K | 6.660 GB | very large, extremely low quality loss |
| [PULSE-7bv5-Q8_0.gguf](https://huggingface.co/tensorblock/OpenMEDLab_PULSE-7bv5-GGUF/blob/main/PULSE-7bv5-Q8_0.gguf) | Q8_0 | 8.620 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/OpenMEDLab_PULSE-7bv5-GGUF --include "PULSE-7bv5-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/OpenMEDLab_PULSE-7bv5-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```