Instructions to use YuyaoGe/SkillForge_Alfworld_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use YuyaoGe/SkillForge_Alfworld_7B with Transformers:

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

pipe = pipeline("text-generation", model="YuyaoGe/SkillForge_Alfworld_7B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("YuyaoGe/SkillForge_Alfworld_7B")
model = AutoModelForCausalLM.from_pretrained("YuyaoGe/SkillForge_Alfworld_7B", 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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use YuyaoGe/SkillForge_Alfworld_7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "YuyaoGe/SkillForge_Alfworld_7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "YuyaoGe/SkillForge_Alfworld_7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/YuyaoGe/SkillForge_Alfworld_7B

SGLang

How to use YuyaoGe/SkillForge_Alfworld_7B 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 "YuyaoGe/SkillForge_Alfworld_7B" \
    --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": "YuyaoGe/SkillForge_Alfworld_7B",
		"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 "YuyaoGe/SkillForge_Alfworld_7B" \
        --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": "YuyaoGe/SkillForge_Alfworld_7B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use YuyaoGe/SkillForge_Alfworld_7B with Docker Model Runner:
```
docker model run hf.co/YuyaoGe/SkillForge_Alfworld_7B
```

SkillForge_Alfworld_7B

Commit History

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Commit History

Add the model card and the overview figure 22e785a

Add the model card and the overview figure 1fc4d20

Add the model card and the overview figure 4b4c535

Add the model card 0c3f186

Upload folder using huggingface_hub a42b20f verified

initial commit c49eb31 verified

Add the model card and the overview figure

22e785a

Add the model card and the overview figure

1fc4d20

Add the model card and the overview figure

4b4c535

Add the model card

0c3f186

Upload folder using huggingface_hub

a42b20f
verified

initial commit

c49eb31
verified