README.md

---
base_model: cnmoro/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k
inference: false
language:
- pt
- en
license: mit
model_creator: cnmoro
model_name: TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k
pipeline_tag: text-generation
quantized_by: afrideva
tags:
- gguf
- ggml
- quantized
- q2_k
- q3_k_m
- q4_k_m
- q5_k_m
- q6_k
- q8_0
---
# cnmoro/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k-GGUF

Quantized GGUF model files for [TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k](https://huggingface.co/cnmoro/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k) from [cnmoro](https://huggingface.co/cnmoro)


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q2_k.gguf](https://huggingface.co/afrideva/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k-GGUF/resolve/main/tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q2_k.gguf) | q2_k | 482.14 MB  |
| [tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q3_k_m.gguf](https://huggingface.co/afrideva/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k-GGUF/resolve/main/tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q3_k_m.gguf) | q3_k_m | 549.85 MB  |
| [tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q4_k_m.gguf](https://huggingface.co/afrideva/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k-GGUF/resolve/main/tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q4_k_m.gguf) | q4_k_m | 667.81 MB  |
| [tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q5_k_m.gguf](https://huggingface.co/afrideva/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k-GGUF/resolve/main/tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q5_k_m.gguf) | q5_k_m | 782.04 MB  |
| [tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q6_k.gguf](https://huggingface.co/afrideva/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k-GGUF/resolve/main/tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q6_k.gguf) | q6_k | 903.41 MB  |
| [tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q8_0.gguf](https://huggingface.co/afrideva/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v3-8k-GGUF/resolve/main/tinyllama-1.1b-intermediate-1.5t-ptbr-instruct-v3-8k.q8_0.gguf) | q8_0 | 1.17 GB  |



## Original Model Card:
Finetuned version of PY007/TinyLlama-1.1B-intermediate-step-715k-1.5T, on a Portuguese instruct dataset, using axolotl.

v0, v1 and v2 were finetuned for the default 2048 context length. For this v3, I have used the existing v2 and finetuned the model on a 8k context length dataset.
It works fairly well, but it's reasoning capabilities are not so strong. It works well for basic RAG / question answering on retrieved content.

Prompt format:

f"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:\n"