Instructions to use intervitens-archive/internlm2-limarp-chat-20b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use intervitens-archive/internlm2-limarp-chat-20b-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 intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf intervitens-archive/internlm2-limarp-chat-20b-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 intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf intervitens-archive/internlm2-limarp-chat-20b-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 intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf intervitens-archive/internlm2-limarp-chat-20b-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 intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use intervitens-archive/internlm2-limarp-chat-20b-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "intervitens-archive/internlm2-limarp-chat-20b-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "intervitens-archive/internlm2-limarp-chat-20b-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M

Ollama
How to use intervitens-archive/internlm2-limarp-chat-20b-GGUF with Ollama:
```
ollama run hf.co/intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use intervitens-archive/internlm2-limarp-chat-20b-GGUF with Docker Model Runner:
```
docker model run hf.co/intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M
```

Lemonade

How to use intervitens-archive/internlm2-limarp-chat-20b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull intervitens-archive/internlm2-limarp-chat-20b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.internlm2-limarp-chat-20b-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

Experimental model, LimaRP LoRA trained on top of internlm2-base-20b with 8192 context length and merged with internlm2-chat-20b.

Prompt format is ChatML.

internlm2-06limarp-1chat-TASK_ARITHM-20b-v0.03

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the task arithmetic merge method using intervitens/internlm2-base-20b-llama as a base.

Models Merged

The following models were included in the merge:

./internlm2-limarp-20b-v0.03
./internlm2-chat-20b-llama

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: ./internlm2-chat-20b-llama
    parameters:
      weight: 1.0
  - model: ./internlm2-limarp-20b-v0.03
    parameters:
      weight: 0.6
merge_method: task_arithmetic
base_model: ./internlm2-base-20b-llama
parameters:
  #normalize: false
  #int8_mask: true
dtype: bfloat16

Downloads last month: 587

GGUF

Model size

20B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Model tree for intervitens-archive/internlm2-limarp-chat-20b-GGUF

Base model

internlm/internlm2-base-20b

Finetuned

intervitens/internlm2-base-20b-llama

Quantized

(1)

this model

Dataset used to train intervitens-archive/internlm2-limarp-chat-20b-GGUF

Paper for intervitens-archive/internlm2-limarp-chat-20b-GGUF

Editing Models with Task Arithmetic

Paper • 2212.04089 • Published Dec 8, 2022 • 9