Instructions to use mradermacher/Llama-PLLuM-70B-chat-2412-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Llama-PLLuM-70B-chat-2412-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Llama-PLLuM-70B-chat-2412-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/Llama-PLLuM-70B-chat-2412-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 mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
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 mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
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 mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/Llama-PLLuM-70B-chat-2412-GGUF with Ollama:
ollama run hf.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use mradermacher/Llama-PLLuM-70B-chat-2412-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/Llama-PLLuM-70B-chat-2412-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Llama-PLLuM-70B-chat-2412-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Llama-PLLuM-70B-chat-2412-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
auto-patch README.md
Browse files
README.md
CHANGED
|
@@ -24,7 +24,7 @@ static quants of https://huggingface.co/CYFRAGOVPL/Llama-PLLuM-70B-chat-2412
|
|
| 24 |
|
| 25 |
***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Llama-PLLuM-70B-chat-2412-GGUF).***
|
| 26 |
|
| 27 |
-
weighted/imatrix quants
|
| 28 |
## Usage
|
| 29 |
|
| 30 |
If you are unsure how to use GGUF files, refer to one of [TheBloke's
|
|
@@ -44,6 +44,7 @@ more details, including on how to concatenate multi-part files.
|
|
| 44 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q4_K_S.gguf) | Q4_K_S | 40.4 | fast, recommended |
|
| 45 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q4_K_M.gguf) | Q4_K_M | 42.6 | fast, recommended |
|
| 46 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q5_K_S.gguf) | Q5_K_S | 48.8 | |
|
|
|
|
| 47 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q6_K.gguf) | Q6_K | 58.0 | very good quality |
|
| 48 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q8_0.gguf) | Q8_0 | 75.1 | fast, best quality |
|
| 49 |
|
|
|
|
| 24 |
|
| 25 |
***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Llama-PLLuM-70B-chat-2412-GGUF).***
|
| 26 |
|
| 27 |
+
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-i1-GGUF
|
| 28 |
## Usage
|
| 29 |
|
| 30 |
If you are unsure how to use GGUF files, refer to one of [TheBloke's
|
|
|
|
| 44 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q4_K_S.gguf) | Q4_K_S | 40.4 | fast, recommended |
|
| 45 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q4_K_M.gguf) | Q4_K_M | 42.6 | fast, recommended |
|
| 46 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q5_K_S.gguf) | Q5_K_S | 48.8 | |
|
| 47 |
+
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q5_K_M.gguf) | Q5_K_M | 50.0 | |
|
| 48 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q6_K.gguf) | Q6_K | 58.0 | very good quality |
|
| 49 |
| [GGUF](https://huggingface.co/mradermacher/Llama-PLLuM-70B-chat-2412-GGUF/resolve/main/Llama-PLLuM-70B-chat-2412.Q8_0.gguf) | Q8_0 | 75.1 | fast, best quality |
|
| 50 |
|