Instructions to use AliesTaha/fable-traces with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AliesTaha/fable-traces with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AliesTaha/fable-traces")
model = AutoModelForCausalLM.from_pretrained("AliesTaha/fable-traces")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AliesTaha/fable-traces with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/AliesTaha/fable-traces

SGLang

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

Docker Model Runner
How to use AliesTaha/fable-traces with Docker Model Runner:
```
docker model run hf.co/AliesTaha/fable-traces
```

🚩 Report: Spam

#11

by usermma - opened 14 days ago

Discussion

usermma

14 days ago

its a troll, its a waste of time, when asking the model a anything, it would only respond with ("did you know that egypt beat australia in world cup")

i even tried to ask it about coding a simple program, still respond with egypt that beat austalia in world cup..

usermma

14 days ago

needs to be deleted..

because in unsloth studio it have a search bar to download a model..

when someone searchs about ("fable")

and sees a name ("fable-traces")

they would download it

but when the user sees it as a troll..

that new user would forget about interest at ai..

so its designed to let the new users forget the interest about trying ai at home..

which inherently means also will not let the new users try more such like training & upload the models...

Needs to be deleted as fastest as possible.. !

usermma

14 days ago

because unsloth studio it doesn't have a feature to filter those ("troll") models..

which inherently the new users will lose their interest about learning more and trying more in . ...

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