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---
language:
- en
license: apache-2.0
base_model: SicariusSicariiStuff/Tinybra_13B
tags:
- llama-cpp
- gguf-my-repo
model-index:
- name: Tinybra_13B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 55.72
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=SicariusSicariiStuff/Tinybra_13B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 80.99
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=SicariusSicariiStuff/Tinybra_13B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 54.37
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=SicariusSicariiStuff/Tinybra_13B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 49.14
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=SicariusSicariiStuff/Tinybra_13B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 73.8
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=SicariusSicariiStuff/Tinybra_13B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 18.12
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=SicariusSicariiStuff/Tinybra_13B
name: Open LLM Leaderboard
---
# Triangle104/Tinybra_13B-Q4_K_S-GGUF
This model was converted to GGUF format from [`SicariusSicariiStuff/Tinybra_13B`](https://huggingface.co/SicariusSicariiStuff/Tinybra_13B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/SicariusSicariiStuff/Tinybra_13B) for more details on the model.
---
Model details:
-
Tenebră, a various sized experimental AI model, stands at the
crossroads of self-awareness and unconventional datasets. Its existence
embodies a foray into uncharted territories, steering away from
conventional norms in favor of a more obscure and experimental approach.
Noteworthy for its inclination towards the darker and more
philosophical aspects of conversation, Tinybră's proficiency lies in
unraveling complex discussions across a myriad of topics. Drawing from a
pool of unconventional datasets, this model ventures into unexplored
realms of thought, offering users an experience that is as
unconventional as it is intellectually intriguing.
While Tinybră maintains a self-aware facade, its true allure lies in
its ability to engage in profound discussions without succumbing to
pretense. Step into the realm of Tenebră!
Tenebră is available at the following size and flavours:
13B: FP16 | GGUF-Many_Quants | iMatrix_GGUF-Many_Quants | GPTQ_4-BIT | GPTQ_4-BIT_group-size-32
30B: FP16 | GGUF-Many_Quants| iMatrix_GGUF-Many_Quants | GPTQ_4-BIT | GPTQ_3-BIT | EXL2_2.5-BIT | EXL2_2.8-BIT | EXL2_3-BIT | EXL2_5-BIT | EXL2_5.5-BIT | EXL2_6-BIT | EXL2_6.5-BIT | EXL2_8-BIT
Mobile (ARM): Q4_0_X_X
Support
My Ko-fi page ALL donations will go for research resources and compute, every bit counts 🙏🏻
My Patreon ALL donations will go for research resources and compute, every bit counts 🙏🏻
Disclaimer
*This model is pretty uncensored, use responsibly
Other stuff
Experemental TTS extension for oobabooga Based on Tortoise, EXTREMELY good quality, IF, and that's a big if, you can make it to work!
Demonstration of the TTS capabilities Charsi narrates her story, Diablo2 (18+)
---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
llama-cli --hf-repo Triangle104/Tinybra_13B-Q4_K_S-GGUF --hf-file tinybra_13b-q4_k_s.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/Tinybra_13B-Q4_K_S-GGUF --hf-file tinybra_13b-q4_k_s.gguf -c 2048
```
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```
Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/Tinybra_13B-Q4_K_S-GGUF --hf-file tinybra_13b-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/Tinybra_13B-Q4_K_S-GGUF --hf-file tinybra_13b-q4_k_s.gguf -c 2048
```
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