Instructions to use nnch/multilingual-e5-large-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nnch/multilingual-e5-large-Q4_K_M-GGUF with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("nnch/multilingual-e5-large-Q4_K_M-GGUF")

sentences = [
    "The weather is lovely today.",
    "It's so sunny outside!",
    "He drove to the stadium."
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use nnch/multilingual-e5-large-Q4_K_M-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 nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nnch/multilingual-e5-large-Q4_K_M-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 nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf nnch/multilingual-e5-large-Q4_K_M-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 nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf nnch/multilingual-e5-large-Q4_K_M-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 nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use nnch/multilingual-e5-large-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use nnch/multilingual-e5-large-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use nnch/multilingual-e5-large-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull nnch/multilingual-e5-large-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.multilingual-e5-large-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

multilingual-e5-large-Q4_K_M-GGUF / tokenizer_config.json

nnch

Create tokenizer_config.json

cc68655 verified almost 2 years ago

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417 Bytes

	{
	"bos_token": "<s>",
	"clean_up_tokenization_spaces": true,
	"cls_token": "<s>",
	"eos_token": "</s>",
	"mask_token": {
	"__type": "AddedToken",
	"content": "<mask>",
	"lstrip": true,
	"normalized": true,
	"rstrip": false,
	"single_word": false
	},
	"model_max_length": 512,
	"pad_token": "<pad>",
	"sep_token": "</s>",
	"tokenizer_class": "XLMRobertaTokenizer",
	"unk_token": "<unk>"
	}