GGUF
English
mistral
instruct
finetune
chatml
gpt4
synthetic data
distillation
dpo
rlhf
TensorBlock
GGUF
Eval Results (legacy)
conversational
Instructions to use tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K # Run inference directly in the terminal: llama cli -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF with Ollama:
ollama run hf.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
- Lemonade
How to use tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF:Q2_K
Run and chat with the model
lemonade run user.NeuralHermes-2.5-Mistral-7B-GGUF-Q2_K
List all available models
lemonade list
- Atomic Chat
Upload folder using huggingface_hub
Browse files- .gitattributes +12 -0
- NeuralHermes-2.5-Mistral-7B-Q2_K.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q3_K_L.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q3_K_M.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q3_K_S.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q4_0.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q4_K_M.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q4_K_S.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q5_0.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q5_K_M.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q5_K_S.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q6_K.gguf +3 -0
- NeuralHermes-2.5-Mistral-7B-Q8_0.gguf +3 -0
- README.md +80 -0
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---
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license: apache-2.0
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base_model: sonthenguyen/NeuralHermes-2.5-Mistral-7B
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tags:
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- TensorBlock
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- GGUF
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---
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<div style="display: flex; justify-content: space-between; width: 100%;">
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<div style="display: flex; flex-direction: column; align-items: flex-start;">
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<p style="margin-top: 0.5em; margin-bottom: 0em;">
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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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</p>
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</div>
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</div>
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## sonthenguyen/NeuralHermes-2.5-Mistral-7B - GGUF
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This repo contains GGUF format model files for [sonthenguyen/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/sonthenguyen/NeuralHermes-2.5-Mistral-7B).
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
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<div style="text-align: left; margin: 20px 0;">
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<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;">
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Run them on the TensorBlock client using your local machine ↗
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</a>
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</div>
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## Prompt template
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```
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<|im_start|>system
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{system_prompt}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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## Model file specification
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| 43 |
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| Filename | Quant type | File Size | Description |
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| 45 |
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| -------- | ---------- | --------- | ----------- |
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| [NeuralHermes-2.5-Mistral-7B-Q2_K.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q2_K.gguf) | Q2_K | 2.719 GB | smallest, significant quality loss - not recommended for most purposes |
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| [NeuralHermes-2.5-Mistral-7B-Q3_K_S.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q3_K_S.gguf) | Q3_K_S | 3.165 GB | very small, high quality loss |
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| [NeuralHermes-2.5-Mistral-7B-Q3_K_M.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q3_K_M.gguf) | Q3_K_M | 3.519 GB | very small, high quality loss |
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| [NeuralHermes-2.5-Mistral-7B-Q3_K_L.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q3_K_L.gguf) | Q3_K_L | 3.822 GB | small, substantial quality loss |
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| [NeuralHermes-2.5-Mistral-7B-Q4_0.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q4_0.gguf) | Q4_0 | 4.109 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
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| [NeuralHermes-2.5-Mistral-7B-Q4_K_S.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q4_K_S.gguf) | Q4_K_S | 4.140 GB | small, greater quality loss |
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| 52 |
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| [NeuralHermes-2.5-Mistral-7B-Q4_K_M.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q4_K_M.gguf) | Q4_K_M | 4.368 GB | medium, balanced quality - recommended |
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| [NeuralHermes-2.5-Mistral-7B-Q5_0.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q5_0.gguf) | Q5_0 | 4.998 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
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| 54 |
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| [NeuralHermes-2.5-Mistral-7B-Q5_K_S.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q5_K_S.gguf) | Q5_K_S | 4.998 GB | large, low quality loss - recommended |
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| 55 |
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| [NeuralHermes-2.5-Mistral-7B-Q5_K_M.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q5_K_M.gguf) | Q5_K_M | 5.131 GB | large, very low quality loss - recommended |
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| 56 |
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| [NeuralHermes-2.5-Mistral-7B-Q6_K.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q6_K.gguf) | Q6_K | 5.942 GB | very large, extremely low quality loss |
|
| 57 |
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| [NeuralHermes-2.5-Mistral-7B-Q8_0.gguf](https://huggingface.co/tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF/blob/main/NeuralHermes-2.5-Mistral-7B-Q8_0.gguf) | Q8_0 | 7.696 GB | very large, extremely low quality loss - not recommended |
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## Downloading instruction
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| 61 |
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### Command line
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| 64 |
+
Firstly, install Huggingface Client
|
| 65 |
+
|
| 66 |
+
```shell
|
| 67 |
+
pip install -U "huggingface_hub[cli]"
|
| 68 |
+
```
|
| 69 |
+
|
| 70 |
+
Then, downoad the individual model file the a local directory
|
| 71 |
+
|
| 72 |
+
```shell
|
| 73 |
+
huggingface-cli download tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF --include "NeuralHermes-2.5-Mistral-7B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
|
| 74 |
+
```
|
| 75 |
+
|
| 76 |
+
If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
|
| 77 |
+
|
| 78 |
+
```shell
|
| 79 |
+
huggingface-cli download tensorblock/NeuralHermes-2.5-Mistral-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
|
| 80 |
+
```
|