Instructions to use QuantFactory/Mistral-Nemo-Instruct-2407-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/Mistral-Nemo-Instruct-2407-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/Mistral-Nemo-Instruct-2407-GGUF",
	filename="Mistral-Nemo-Instruct-2407.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 QuantFactory/Mistral-Nemo-Instruct-2407-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Mistral-Nemo-Instruct-2407-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 QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Mistral-Nemo-Instruct-2407-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 QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/Mistral-Nemo-Instruct-2407-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
```

Unsloth Studio

How to use QuantFactory/Mistral-Nemo-Instruct-2407-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 QuantFactory/Mistral-Nemo-Instruct-2407-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 QuantFactory/Mistral-Nemo-Instruct-2407-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/Mistral-Nemo-Instruct-2407-GGUF to start chatting

Docker Model Runner
How to use QuantFactory/Mistral-Nemo-Instruct-2407-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/Mistral-Nemo-Instruct-2407-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Mistral-Nemo-Instruct-2407-GGUF-Q4_K_M

List all available models

lemonade list

Error loading model in llama.cpp ?

by ubergarm - opened Jul 20, 2024

Discussion

ubergarm

Jul 20, 2024

Was this quantized with iamlemec's 6515e787 commit ?

Just failed running it on llama.cpp 69c487 as well as above commit.

llama_model_load: error loading model: check_tensor_dims: tensor 'blk.0.attn_q.weight' has wrong shape; expected  5120,  5120, got  5120,  4096,     1,     1
llama_load_model_from_file: failed to load model
llama_init_from_gpt_params: error: failed to load model '../models/QuantFactory/Mistral-Nemo-Instruct-2407-GGUF/Mistral-Nemo-Instruct-2407.Q8_0.gguf'

$ cd llama.cpp
$ git pull
$ git remote add iamlemec git@github.com:iamlemec/llama.cpp.git
$ git cherry-pick 6515e787d10095d439228f2
$ git log --pretty=oneline | head -n 5
7c9f8d3c3775c38cb014285752ea88319d5275f8 mistral nemo inference support
69c487f4ed57bb4d4514a1b7ff12608d5a8e7ef0 CUDA: MMQ code deduplication + iquant support (#8495)
07283b1a90e1320aae4762c7e03c879043910252 gguf : handle null name during init (#8587)
940362224d20e35f13aa5fd34a0d937ae57bdf7d llama : add support for Tekken pre-tokenizer (#8579)
69b9945b44c3057ec17cb556994cd36060455d44 llama.swiftui: fix end of generation bug (#8268)
$ make clean && time GGML_CUDA=1 make -j$(nproc)
<error from above>

I suppose I could just wait a bit for everything to catch up, hah.. Thanks for any tips.

ubergarm

Jul 20, 2024

I got this one working in llama.cpp CompendiumLabs/mistral-nemo-instruct-2407-gguf

munish0838

Quant Factory org Jul 21, 2024

@ubergarm converted these using imalemec's forck, can you confirm if these work for you
QuantFactory/Mistral-Nemo-Instruct-2407-GGUF-iamlemec

ubergarm

Jul 21, 2024

@munish0838 huh I downloaded the new q8_0 and then noticed it has the same sha256sum as the existing one in this repo...

Mistral-Nemo-Instruct-2407-GGUF
Mistral-Nemo-Instruct-2407-GGUF-iamlemec

Same is true for a couple other quants I checked. The sha256sum of your q5_0 does not match that of iamlemec's CompendiumLabs one (if quantizing is reproducable deterministic?). Huh, MaziyarPanahi hasn't uploaded yet either, I saw him mentioning a bug in one of the GH Issue threads... I am not sure how iamlemec did it then if it wasn't that fork?? hrmm... i'll have to look closer at the diff, maybe there is a new argument needed ???

In the mean time, I'll try your q5_0 and see if that one works by some random chance... It is a puzzle to me!