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leonsarmiento/TimeCapsuleLLM-v2-llama-1.2B-8bit-mlx
TimeCapsuleLLM-v2-llama-1.2B-8bit-mlx is a text generation model from leonsarmiento. Use it when you need the model to write or continue text. It is set up for mlx.
This model was converted to MLX format from haykgrigorian/TimeCapsuleLLM-v2-llama-1.2B using 8-bit uniform quantization optimized for Apple Silicon.
Downloads · 30 days
33
14% of all-time downloads
All-time downloads
231
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1.2B
1.2 GB on disk
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How the weights are stored.
U321.2B · 100%
From the Hugging Face model README
This model was converted to MLX format from haykgrigorian/TimeCapsuleLLM-v2-llama-1.2B using 8-bit uniform quantization optimized for Apple Silicon.
TimeCapsuleLLM-v2-llama-1.2B is a 1.2B-parameter Llama-architecture model trained from scratch on 112 GB of historical English texts from London (1800–1875). It features 22 layers, Grouped Query Attention (GQA) with 16 query / 8 KV heads, and a custom BPE tokenizer (32K vocab). The model generates text in the style of historical English from that era.
pip install -U mlx-lm
python -m mlx_lm.generate --model leonsarmiento/TimeCapsuleLLM-v2-llama-1.2B-8bit-mlx --max-tokens 256 --temperature 0.5 --prompt "The streets of London were"
| Metric | Value |
|---|---|
| Quantization type | 8-bit uniform |
| Average | 8.501 bits per weight |
| Group size | 64 |
| Method | mlx_lm |
| Total output size | ~1.2 GB (1 shard) |
This is a base completion model — it performs raw text continuation. In LM Studio, use completion mode or select the Llama 2 template for best results.
| Parameter | Value |
|---|---|
temperature | 0.7 |
top_p | 0.9 |
top_k | 64 |
min_p | 0.01 |
max_tokens | 200+ |