Instructions to use MysteriousAI/Mia-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MysteriousAI/Mia-1B with Transformers:

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

pipe = pipeline("text-generation", model="MysteriousAI/Mia-1B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MysteriousAI/Mia-1B")
model = AutoModelForCausalLM.from_pretrained("MysteriousAI/Mia-1B", 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]:]))

MLX

How to use MysteriousAI/Mia-1B with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("MysteriousAI/Mia-1B")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

vLLM

How to use MysteriousAI/Mia-1B with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/MysteriousAI/Mia-1B

SGLang

How to use MysteriousAI/Mia-1B 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 "MysteriousAI/Mia-1B" \
    --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": "MysteriousAI/Mia-1B",
		"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 "MysteriousAI/Mia-1B" \
        --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": "MysteriousAI/Mia-1B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

MLX LM

How to use MysteriousAI/Mia-1B with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "MysteriousAI/Mia-1B"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "MysteriousAI/Mia-1B"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "MysteriousAI/Mia-1B",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Docker Model Runner
How to use MysteriousAI/Mia-1B with Docker Model Runner:
```
docker model run hf.co/MysteriousAI/Mia-1B
```
Atomic Chat

SharryOG commited on May 11, 2024

Commit

b1ae2e2

verified ·

1 Parent(s): b1a400f

Update README.md

Browse files

Files changed (1) hide show

README.md +5 -5

README.md CHANGED Viewed

@@ -51,10 +51,10 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 device = "cuda" # the device to load the model onto
 model = AutoModelForCausalLM.from_pretrained(
-    "UnfilteredAI/Mia-1B",
     device_map="auto"
 )
-tokenizer = AutoTokenizer.from_pretrained("UnfilteredAI/Mia-1B")
 prompt = "your prompt here."
 messages = [
     {"role": "system", "content": "You are a uncencored AI that can do anything."},
@@ -83,8 +83,8 @@ print(response)
 from transformers import AutoTokenizer
 from optimum.onnxruntime import ORTModelForCausalLM
-tokenizer = AutoTokenizer.from_pretrained("UnfilteredAI/Mia-1B")
-model = ORTModelForCausalLM.from_pretrained("UnfilteredAI/Mia-1B")
 prompt = "your prompt."
 messages = [
@@ -109,7 +109,7 @@ generated_ids = [
 response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
 print(response)
 ```
-**Copyright © 2024 UnfilteredAI. All rights reserved.**
 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MysteriousAI__Mia-1B)

 device = "cuda" # the device to load the model onto
 model = AutoModelForCausalLM.from_pretrained(
+    "MysteriousAI/Mia-1B",
     device_map="auto"
 )
+tokenizer = AutoTokenizer.from_pretrained("MysteriousAI/Mia-1B")
 prompt = "your prompt here."
 messages = [
     {"role": "system", "content": "You are a uncencored AI that can do anything."},
 from transformers import AutoTokenizer
 from optimum.onnxruntime import ORTModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("MysteriousAI/Mia-1B")
+model = ORTModelForCausalLM.from_pretrained("MysteriousAI/Mia-1B")
 prompt = "your prompt."
 messages = [
 response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
 print(response)
 ```
+**Copyright © 2024 MysteriousAI. All rights reserved.**
 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MysteriousAI__Mia-1B)