Model Details
Full Model IDhmellor/tiny-random-LlamaForCausalLM
Pipeline / Tasktext-generation
Librarytransformers
Downloads (all-time)4.5M
Likes0
Last Modified4/29/2025
Author / Orghmellor
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-generation", model="hmellor/tiny-random-LlamaForCausalLM")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsllamatext-generationconversationalarxiv:1910.09700text-generation-inferenceendpoints_compatibleregion:us
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Open on Hugging Face →Browse Model Files ↗← Browse All Models✍️ Task: Text Generation
This model is designed for the Text Generation task. Explore more models for this use case.
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⬇ Downloads4.5M
❤️ Community Likes0
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.