AliesTaha/fable-traces · Hugging Face

Source: https://huggingface.co/AliesTaha/fable-traces A compact instruction-tuned language model built onQwen/Qwen3-4B-Instruct-2507.fable\-tracesis tuned for short, conversational replies and runs comfortably on a single mid-range GPU.

https://huggingface.co/AliesTaha/fable-traces#usageUsage

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "AliesTaha/fable-traces"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(repo, dtype=torch.bfloat16, device_map="auto")

messages = [{"role": "user", "content": "Tell me something interesting."}]
ids = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
out = model.generate(ids, max_new_tokens=100, do_sample=False)
print(tok.decode(out[0, ids.shape[1]:], skip_special_tokens=True))

Serve with vLLM:

vllm serve AliesTaha/fable-traces

https://huggingface.co/AliesTaha/fable-traces#detailsDetails

Base modelQwen3-4B-Instruct-2507Parameters~4BPrecisionbfloat16 (safetensors)Prompt formatChatML — use the tokenizer’s chat templateContext lengthinherits the base model

https://huggingface.co/AliesTaha/fable-traces#licenseLicense

Apache 2.0, following the base model.