Instructions to use TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ")
model = AutoModelForCausalLM.from_pretrained("TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ

SGLang

How to use TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ with Docker Model Runner:
```
docker model run hf.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ
```

I can't get it running in text-generation-webui

by mamsds - opened Dec 15, 2023

Discussion

mamsds

Dec 15, 2023

I tried to follow all the instructions carefully and I download the model using text-generation-webui's "Model" tab, still I get the follow error:

Traceback (most recent call last):

File "/mnt/models/text-generation-webui/modules/ui_model_menu.py", line 237, in download_model_wrapper

model, branch = downloader.sanitize_model_and_branch_names(repo_id, None)

                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

File "/mnt/models/text-generation-webui/download-model.py", line 39, in sanitize_model_and_branch_names

if model[-1] == '/':

   ~~~~~^^^^

IndexError: string index out of range

Any thoughts?

Hypersniper

Dec 16, 2023

same here

1NoobArtist

Jan 3, 2024

Getting this error:

23:25:45-094355 INFO Loading TheBloke_Mixtral-8x7B-Instruct-v0.1-GPTQ
23:25:45-609266 ERROR Failed to load the model.
Traceback (most recent call last):
File "E:\text-generation-webui-main\text-generation-webui-main\modules\ui_model_menu.py", line 214, in load_model_wrapper
shared.model, shared.tokenizer = load_model(selected_model, loader)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "E:\text-generation-webui-main\text-generation-webui-main\modules\models.py", line 90, in load_model
output = load_func_maploader
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "E:\text-generation-webui-main\text-generation-webui-main\modules\models.py", line 399, in ExLlama_HF_loader
return ExllamaHF.from_pretrained(model_name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "E:\text-generation-webui-main\text-generation-webui-main\modules\exllama_hf.py", line 174, in from_pretrained
return ExllamaHF(config)
^^^^^^^^^^^^^^^^^
File "E:\text-generation-webui-main\text-generation-webui-main\modules\exllama_hf.py", line 31, in init
self.ex_model = ExLlama(self.ex_config)
^^^^^^^^^^^^^^^^^^^^^^^
File "E:\text-generation-webui-main\text-generation-webui-main\installer_files\env\Lib\site-packages\exllama\model.py", line 753, in init
decoder_size += math.prod(shape) * _layer_dtype_size(key)
^^^^^^^^^^^^^^^^^^^^^^
File "E:\text-generation-webui-main\text-generation-webui-main\installer_files\env\Lib\site-packages\exllama\model.py", line 716, in _layer_dtype_size
raise ValueError("Unrecognized layer: " + key)
ValueError: Unrecognized layer: model.layers.0.block_sparse_moe.experts.0.w1.bias

FelipeAr4n

Jan 20, 2024

•

edited Jan 20, 2024

ERROR Failed to load the model.
Traceback (most recent call last):
File "D:\text-generation-webui-main\modules\ui_model_menu.py", line 213, in load_model_wrapper
shared.model, shared.tokenizer = load_model(selected_model, loader)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\modules\models.py", line 87, in load_model
output = load_func_maploader
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\modules\models.py", line 250, in llamacpp_loader
model, tokenizer = LlamaCppModel.from_pretrained(model_file)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\text-generation-webui-main\modules\llamacpp_model.py", line 63, in from_pretrained
Llama = llama_cpp_lib().Llama
^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'Llama'

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