Instructions to use thoughtworks/MiniMax-M2.5-Eagle3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use thoughtworks/MiniMax-M2.5-Eagle3 with Transformers:

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

pipe = pipeline("text-generation", model="thoughtworks/MiniMax-M2.5-Eagle3")

# Load model directly
from transformers import AutoTokenizer, LlamaForCausalLMEagle3

tokenizer = AutoTokenizer.from_pretrained("thoughtworks/MiniMax-M2.5-Eagle3")
model = LlamaForCausalLMEagle3.from_pretrained("thoughtworks/MiniMax-M2.5-Eagle3")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use thoughtworks/MiniMax-M2.5-Eagle3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "thoughtworks/MiniMax-M2.5-Eagle3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "thoughtworks/MiniMax-M2.5-Eagle3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/thoughtworks/MiniMax-M2.5-Eagle3

SGLang

How to use thoughtworks/MiniMax-M2.5-Eagle3 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 "thoughtworks/MiniMax-M2.5-Eagle3" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "thoughtworks/MiniMax-M2.5-Eagle3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "thoughtworks/MiniMax-M2.5-Eagle3" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "thoughtworks/MiniMax-M2.5-Eagle3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use thoughtworks/MiniMax-M2.5-Eagle3 with Docker Model Runner:
```
docker model run hf.co/thoughtworks/MiniMax-M2.5-Eagle3
```

lujangusface commited on Apr 11

Commit

2fcf070

verified ·

1 Parent(s): c5e920c

fix: correct pip install command and --dtype fp8 -> --quantization fp8

Browse files

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -31,7 +31,7 @@ Requires our [SGLang fork](https://github.com/tails-mpt/sglang) for MiniMax-M2.5
 **B=1 server** (wide tree — optimal for single-user, real-time requests):
 ```bash
-pip install git+https://github.com/tails-mpt/sglang.git
 python -m sglang.launch_server \
     --model-path MiniMaxAI/MiniMax-M2.5 \
@@ -40,7 +40,7 @@ python -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-num-draft-tokens 8 \
     --speculative-eagle-topk 4 \
-    --dtype fp8 \
     --tp 4 \
     --port 30000
 ```
@@ -55,7 +55,7 @@ python -m sglang.launch_server \
     --speculative-num-steps 5 \
     --speculative-num-draft-tokens 6 \
     --speculative-eagle-topk 1 \
-    --dtype fp8 \
     --tp 4 \
     --port 30002
 ```

 **B=1 server** (wide tree — optimal for single-user, real-time requests):
 ```bash
+pip install 'git+https://github.com/tails-mpt/sglang.git#subdirectory=python'
 python -m sglang.launch_server \
     --model-path MiniMaxAI/MiniMax-M2.5 \
     --speculative-num-steps 3 \
     --speculative-num-draft-tokens 8 \
     --speculative-eagle-topk 4 \
+    --quantization fp8 \
     --tp 4 \
     --port 30000
 ```
     --speculative-num-steps 5 \
     --speculative-num-draft-tokens 6 \
     --speculative-eagle-topk 1 \
+    --quantization fp8 \
     --tp 4 \
     --port 30002
 ```