Instructions to use tensorblock/tiny-random-cohere-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorblock/tiny-random-cohere-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensorblock/tiny-random-cohere-GGUF", dtype="auto") - llama-cpp-python
How to use tensorblock/tiny-random-cohere-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tensorblock/tiny-random-cohere-GGUF", filename="tiny-random-cohere-Q2_K.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tensorblock/tiny-random-cohere-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tensorblock/tiny-random-cohere-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf tensorblock/tiny-random-cohere-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tensorblock/tiny-random-cohere-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf tensorblock/tiny-random-cohere-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/tiny-random-cohere-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf tensorblock/tiny-random-cohere-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/tiny-random-cohere-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf tensorblock/tiny-random-cohere-GGUF:Q2_K
Use Docker
docker model run hf.co/tensorblock/tiny-random-cohere-GGUF:Q2_K
- LM Studio
- Jan
- Ollama
How to use tensorblock/tiny-random-cohere-GGUF with Ollama:
ollama run hf.co/tensorblock/tiny-random-cohere-GGUF:Q2_K
- Unsloth Studio
How to use tensorblock/tiny-random-cohere-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tensorblock/tiny-random-cohere-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for tensorblock/tiny-random-cohere-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tensorblock/tiny-random-cohere-GGUF to start chatting
- Docker Model Runner
How to use tensorblock/tiny-random-cohere-GGUF with Docker Model Runner:
docker model run hf.co/tensorblock/tiny-random-cohere-GGUF:Q2_K
- Lemonade
How to use tensorblock/tiny-random-cohere-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tensorblock/tiny-random-cohere-GGUF:Q2_K
Run and chat with the model
lemonade run user.tiny-random-cohere-GGUF-Q2_K
List all available models
lemonade list
File size: 6,725 Bytes
e575784 1130e48 e575784 76987c1 0cf96f4 76987c1 0cf96f4 76987c1 e575784 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 | ---
library_name: transformers
tags:
- TensorBlock
- GGUF
base_model: hyper-accel/tiny-random-cohere
---
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## hyper-accel/tiny-random-cohere - GGUF
This repo contains GGUF format model files for [hyper-accel/tiny-random-cohere](https://huggingface.co/hyper-accel/tiny-random-cohere).
The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4882](https://github.com/ggml-org/llama.cpp/commit/be7c3034108473beda214fd1d7c98fd6a7a3bdf5).
## Our projects
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## Prompt template
```
<BOS_TOKEN><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{system_prompt}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>{prompt}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>
```
## Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [tiny-random-cohere-Q2_K.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q2_K.gguf) | Q2_K | 0.121 GB | smallest, significant quality loss - not recommended for most purposes |
| [tiny-random-cohere-Q3_K_S.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q3_K_S.gguf) | Q3_K_S | 0.121 GB | very small, high quality loss |
| [tiny-random-cohere-Q3_K_M.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q3_K_M.gguf) | Q3_K_M | 0.122 GB | very small, high quality loss |
| [tiny-random-cohere-Q3_K_L.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q3_K_L.gguf) | Q3_K_L | 0.122 GB | small, substantial quality loss |
| [tiny-random-cohere-Q4_0.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q4_0.gguf) | Q4_0 | 0.122 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [tiny-random-cohere-Q4_K_S.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q4_K_S.gguf) | Q4_K_S | 0.122 GB | small, greater quality loss |
| [tiny-random-cohere-Q4_K_M.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q4_K_M.gguf) | Q4_K_M | 0.123 GB | medium, balanced quality - recommended |
| [tiny-random-cohere-Q5_0.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q5_0.gguf) | Q5_0 | 0.123 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [tiny-random-cohere-Q5_K_S.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q5_K_S.gguf) | Q5_K_S | 0.123 GB | large, low quality loss - recommended |
| [tiny-random-cohere-Q5_K_M.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q5_K_M.gguf) | Q5_K_M | 0.123 GB | large, very low quality loss - recommended |
| [tiny-random-cohere-Q6_K.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q6_K.gguf) | Q6_K | 0.124 GB | very large, extremely low quality loss |
| [tiny-random-cohere-Q8_0.gguf](https://huggingface.co/tensorblock/tiny-random-cohere-GGUF/blob/main/tiny-random-cohere-Q8_0.gguf) | Q8_0 | 0.157 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/tiny-random-cohere-GGUF --include "tiny-random-cohere-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/tiny-random-cohere-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```
|