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Model: ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF
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MIT License
Copyright (c) 2025 Hayk Grigorian
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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---
base_model: haykgrigorian/TimeCapsuleLLM-v2-llama-1.2B
language:
- en
library_name: transformers
license: mit
datasets:
- postgrammar/london-llm-1800
quantized_by: ncky
tags:
- text-generation-inference
- transformers
- llama
- gguf
- historical
---
## About
static and imatrix-assisted GGUF quants of https://huggingface.co/haykgrigorian/TimeCapsuleLLM-v2-llama-1.2B.
Generated with `llama.cpp` build `8044` (`91ea5d67f`).
`IQ4_XS` was quantized with an imatrix generated on 19th-century public-domain English text.
Note: this model has FFN dimensions (`5504`) not divisible by `256`, so `llama.cpp` applied fallback quantization to 22 tensors for K/IQ quant types.
## Base Model Info (from original model card)
Source: https://huggingface.co/haykgrigorian/TimeCapsuleLLM-v2-llama-1.2B
| Detail | Value |
| :--- | :--- |
| Model Architecture | LlamaForCausalLM (decoder-only transformer) |
| Parameter Count | ~1.22B |
| Training Type | Trained from scratch (random initialization) |
| Tokenizer | Custom BPE, vocab size 32,000 |
| Sequence Length | 2048 |
| Attention Type | Grouped Query Attention (16 Q heads / 8 KV heads) |
| Hidden Size | 2048 |
| Intermediate Size | 5504 |
| Layers | 22 |
Training details reported by the source model card:
- Final training loss: 3.3951
- Start training loss: 10.7932
- Training steps: 182,000
- Epochs: 0.4997
- Training time: 117h 51m
- Reported training cost: $340.97 on an H100 SXM (RunPod)
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details.
## Provided Quants
(sorted by size, not necessarily quality)
| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q2_K.gguf) | Q2_K | 0.5 | smallest |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q3_K_S.gguf) | Q3_K_S | 0.6 | low VRAM |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q3_K_M.gguf) | Q3_K_M | 0.6 | balanced low size |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q3_K_L.gguf) | Q3_K_L | 0.6 | better than Q3_K_M |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.IQ4_XS.gguf) | IQ4_XS | 0.6 | imatrix, recommended at this size |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q4_K_S.gguf) | Q4_K_S | 0.7 | fast, recommended |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q4_K_M.gguf) | Q4_K_M | 0.7 | fast, recommended |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q5_K_S.gguf) | Q5_K_S | 0.8 | higher quality |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q5_K_M.gguf) | Q5_K_M | 0.9 | higher quality |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q6_K.gguf) | Q6_K | 1.0 | very good quality |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.Q8_0.gguf) | Q8_0 | 1.2 | fast, best quality |
| [GGUF](https://huggingface.co/ncky/TimeCapsuleLLM-v2-llama-1.2B-GGUF/resolve/main/TimeCapsuleLLM-v2-llama-1.2B.f16.gguf) | f16 | 2.3 | 16 bpw, overkill |

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