Instructions to use RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-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 RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-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 RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-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 RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-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 RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-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 RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M

Use Docker

docker model run hf.co/RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf with Ollama:
```
ollama run hf.co/RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf with Docker Model Runner:
```
docker model run hf.co/RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M
```

Lemonade

How to use RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RichardErkhov/setfunctionenvironment_-_NeMoria-21b-base-gguf:Q4_K_M

Run and chat with the model

lemonade run user.setfunctionenvironment_-_NeMoria-21b-base-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

Quantization made by Richard Erkhov.

Github

Discord

Request more models

NeMoria-21b-base - GGUF

Model creator: https://huggingface.co/setfunctionenvironment/
Original model: https://huggingface.co/setfunctionenvironment/NeMoria-21b-base/

Name	Quant method	Size
NeMoria-21b-base.Q2_K.gguf	Q2_K	7.26GB
NeMoria-21b-base.IQ3_XS.gguf	IQ3_XS	8.05GB
NeMoria-21b-base.IQ3_S.gguf	IQ3_S	8.47GB
NeMoria-21b-base.Q3_K_S.gguf	Q3_K_S	8.43GB
NeMoria-21b-base.IQ3_M.gguf	IQ3_M	8.73GB
NeMoria-21b-base.Q3_K.gguf	Q3_K	9.33GB
NeMoria-21b-base.Q3_K_M.gguf	Q3_K_M	9.33GB
NeMoria-21b-base.Q3_K_L.gguf	Q3_K_L	10.1GB
NeMoria-21b-base.IQ4_XS.gguf	IQ4_XS	10.44GB
NeMoria-21b-base.Q4_0.gguf	Q4_0	10.87GB
NeMoria-21b-base.IQ4_NL.gguf	IQ4_NL	10.98GB
NeMoria-21b-base.Q4_K_S.gguf	Q4_K_S	10.94GB
NeMoria-21b-base.Q4_K.gguf	Q4_K	11.51GB
NeMoria-21b-base.Q4_K_M.gguf	Q4_K_M	11.51GB
NeMoria-21b-base.Q4_1.gguf	Q4_1	12.02GB
NeMoria-21b-base.Q5_0.gguf	Q5_0	13.17GB
NeMoria-21b-base.Q5_K_S.gguf	Q5_K_S	13.17GB
NeMoria-21b-base.Q5_K.gguf	Q5_K	13.5GB
NeMoria-21b-base.Q5_K_M.gguf	Q5_K_M	13.5GB
NeMoria-21b-base.Q5_1.gguf	Q5_1	14.32GB
NeMoria-21b-base.Q6_K.gguf	Q6_K	15.62GB
NeMoria-21b-base.Q8_0.gguf	Q8_0	20.22GB

Original model description:

base_model:

unsloth/Mistral-Nemo-Base-2407 library_name: transformers tags:
mergekit
merge

credits 2 https://huggingface.co/TheSkullery/NeMoria-21b smae thing but just base

merge

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

Merge Details

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

unsloth/Mistral-Nemo-Base-2407

Configuration

The following YAML configuration was used to produce this model:

dtype: bfloat16
merge_method: passthrough
slices:
- sources:
  - layer_range: [0, 30]
    model: unsloth/Mistral-Nemo-Base-2407
- sources:
  - layer_range: [16, 32]
    model: unsloth/Mistral-Nemo-Base-2407
    parameters:
      scale:
      - filter: o_proj
        value: 0.0
      - filter: down_proj
        value: 0.0
      - value: 1.0
- sources:
  - layer_range: [16, 32]
    model: unsloth/Mistral-Nemo-Base-2407
    parameters:
      scale:
      - filter: o_proj
        value: 0.0
      - filter: down_proj
        value: 0.0
      - value: 1.0
- sources:
  - layer_range: [32, 40]
    model: unsloth/Mistral-Nemo-Base-2407

Downloads last month: 168

GGUF

Model size

20B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

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