Instructions to use almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4 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 almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4: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 almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4: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 almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M

Use Docker

docker model run hf.co/almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M

LM Studio
Jan
Ollama
How to use almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4 with Ollama:
```
ollama run hf.co/almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4 with Docker Model Runner:
```
docker model run hf.co/almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M
```

Lemonade

How to use almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4:Q4_K_M

Run and chat with the model

lemonade run user.Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4-Q4_K_M

List all available models

lemonade list

Atomic Chat

Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4

File size: 378 Bytes

cfd99fc


FROM ./almedamine/Llama_3.1_8b_Instruct_RCM.VSP_tuned_v0.4/unsloth.F16.gguf
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ .Response }}<|im_end|>
"""
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|im_end|>"
PARAMETER temperature 1.5
PARAMETER min_p 0.1