Quick Start

python
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from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "fableforge-ai/ShellWhisperer-1.5B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")

prompt = """You are an AI agent. Complete the following task:

Task: Write a Python function to calculate the Fibonacci sequence.

Reasoning:"""

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.6, top_p=0.9)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Use Cases

• Shell command completion and suggestion
• Terminal error diagnosis and fix suggestion
• Infrastructure-as-code generation
• DevOps automation assistance

Integration with FableForge Ecosystem

python
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from fableforge_agent_runtime import AgentRuntime
from fableforge_agent_skills import SkillLibrary

runtime = AgentRuntime(
    model="fableforge-ai/ShellWhisperer-1.5B",
    skills=SkillLibrary.all(),
    verification=True
)

result = runtime.run("Deploy a web server on AWS")
print(result.output)
print(result.verification_score)

Ecosystem Integration

Part of the FableForge Agent Ecosystem - 21 open-source projects for building, testing, and deploying AI agents.

Model Details

Limitations

• May generate incorrect code -- always use with verifyloop for critical tasks
• Trained primarily on English data; multilingual performance is limited
• Can hallucinate API signatures or tool parameters
• Not suitable for medical, legal, or financial advice without human review

Citation

bibtex
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@misc{shellwhisperer1.5b2024,
  title={ShellWhisperer-1.5B: Agent Orchestration via Fine-Tuned Language Models},
  author={FableForge Team},
  year={2024},
  url={https://huggingface.co/fableforge-ai/ShellWhisperer-1.5B}
}

License

MIT License - see LICENSE for details.

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Built with hammer by the Anvil team. Part of the FableForge ecosystem.