Instructions to use twanghcmut/mistral-mixlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use twanghcmut/mistral-mixlora with Transformers:

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

pipe = pipeline("text-generation", model="twanghcmut/mistral-mixlora")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("twanghcmut/mistral-mixlora")
model = AutoModelForCausalLM.from_pretrained("twanghcmut/mistral-mixlora")
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 twanghcmut/mistral-mixlora with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/twanghcmut/mistral-mixlora

SGLang

How to use twanghcmut/mistral-mixlora 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 "twanghcmut/mistral-mixlora" \
    --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": "twanghcmut/mistral-mixlora",
		"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 "twanghcmut/mistral-mixlora" \
        --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": "twanghcmut/mistral-mixlora",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use twanghcmut/mistral-mixlora with Docker Model Runner:
```
docker model run hf.co/twanghcmut/mistral-mixlora
```

twanghcmut commited on Nov 20, 2025

Commit

05dee2f

verified ·

1 Parent(s): 640f8c5

End of training

Browse files

Files changed (1) hide show

2025-11-20/17-09-25/train_mistral_mixlora.log +1 -0

2025-11-20/17-09-25/train_mistral_mixlora.log CHANGED Viewed

@@ -2,3 +2,4 @@
 [2025-11-20 17:10:48,481][accelerate.utils.other][WARNING] - Detected kernel version 4.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
 [2025-11-20 17:22:31,608][huggingface_hub.hf_api][WARNING] - No files have been modified since last commit. Skipping to prevent empty commit.
 [2025-11-20 17:24:52,613][accelerate.utils.modeling][INFO] - We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk).

 [2025-11-20 17:10:48,481][accelerate.utils.other][WARNING] - Detected kernel version 4.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
 [2025-11-20 17:22:31,608][huggingface_hub.hf_api][WARNING] - No files have been modified since last commit. Skipping to prevent empty commit.
 [2025-11-20 17:24:52,613][accelerate.utils.modeling][INFO] - We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk).
+[2025-11-20 17:32:33,428][huggingface_hub.hf_api][WARNING] - No files have been modified since last commit. Skipping to prevent empty commit.