Instructions to use TheBloke/Mistral-7B-OpenOrca-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBloke/Mistral-7B-OpenOrca-AWQ with Transformers:

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

pipe = pipeline("text-generation", model="TheBloke/Mistral-7B-OpenOrca-AWQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheBloke/Mistral-7B-OpenOrca-AWQ")
model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-OpenOrca-AWQ")
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/Mistral-7B-OpenOrca-AWQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBloke/Mistral-7B-OpenOrca-AWQ"
# 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/Mistral-7B-OpenOrca-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TheBloke/Mistral-7B-OpenOrca-AWQ

SGLang

How to use TheBloke/Mistral-7B-OpenOrca-AWQ 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/Mistral-7B-OpenOrca-AWQ" \
    --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/Mistral-7B-OpenOrca-AWQ",
		"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/Mistral-7B-OpenOrca-AWQ" \
        --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/Mistral-7B-OpenOrca-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TheBloke/Mistral-7B-OpenOrca-AWQ with Docker Model Runner:
```
docker model run hf.co/TheBloke/Mistral-7B-OpenOrca-AWQ
```

Exception running on cpu

by fulltoos81 - opened Oct 6, 2023

Discussion

fulltoos81

Oct 6, 2023

AutoAWQ installed, cudatoolkit installed.
as per instrucions.
Traceback (most recent call last):
File "/usr/local/apps/mistral-awq/main.py", line 1, in
from awq import AutoAWQForCausalLM
File "/root/miniconda3/envs/mistral/lib/python3.11/site-packages/awq/init.py", line 2, in
from awq.models.auto import AutoAWQForCausalLM
File "/root/miniconda3/envs/mistral/lib/python3.11/site-packages/awq/models/init.py", line 1, in
from .mpt import MptAWQForCausalLM
File "/root/miniconda3/envs/mistral/lib/python3.11/site-packages/awq/models/mpt.py", line 1, in
from .base import BaseAWQForCausalLM
File "/root/miniconda3/envs/mistral/lib/python3.11/site-packages/awq/models/base.py", line 11, in
from awq.quantize.quantizer import AwqQuantizer
File "/root/miniconda3/envs/mistral/lib/python3.11/site-packages/awq/quantize/quantizer.py", line 11, in
from awq.modules.linear import WQLinear_GEMM, WQLinear_GEMV
File "/root/miniconda3/envs/mistral/lib/python3.11/site-packages/awq/modules/linear.py", line 4, in
import awq_inference_engine # with CUDA kernels
^^^^^^^^^^^^^^^^^^^^^^^^^^^
ImportError: libcudart.so.11.0: cannot open shared object file: No such file or directory

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