Instructions to use ForgeWorks/ForgePlex-M2.1-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ForgeWorks/ForgePlex-M2.1-10M with Transformers:

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

pipe = pipeline("text-generation", model="ForgeWorks/ForgePlex-M2.1-10M", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("ForgeWorks/ForgePlex-M2.1-10M", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ForgeWorks/ForgePlex-M2.1-10M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ForgeWorks/ForgePlex-M2.1-10M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ForgeWorks/ForgePlex-M2.1-10M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ForgeWorks/ForgePlex-M2.1-10M

SGLang

How to use ForgeWorks/ForgePlex-M2.1-10M 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 "ForgeWorks/ForgePlex-M2.1-10M" \
    --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": "ForgeWorks/ForgePlex-M2.1-10M",
		"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 "ForgeWorks/ForgePlex-M2.1-10M" \
        --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": "ForgeWorks/ForgePlex-M2.1-10M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ForgeWorks/ForgePlex-M2.1-10M with Docker Model Runner:
```
docker model run hf.co/ForgeWorks/ForgePlex-M2.1-10M
```

Jsandero commited on 12 days ago

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@@ -20,7 +20,7 @@ pipeline_tag: text-generation
 # ForgePlex-M2.1-10M
-**ForgePlex-M2.1-10M** is a 9.99M-parameter decoder-only language model from ForgeWorks, and the most complete model we've built so far. We thank the ForgeWorks team alongside anyone who delivered assistance in the creation of this model.
 # Why not name it ForgePlex-M3?

 # ForgePlex-M2.1-10M
+**ForgePlex-M2.1-10M** is a 9.99M-parameter decoder-only language model from ForgeWorks, trained on 40b tokens. This is the most complete model we've built so far. We thank the ForgeWorks team alongside anyone who delivered assistance in the creation of this model.
 # Why not name it ForgePlex-M3?