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-Q6_K-GGUF
This model was converted to GGUF format from SicariusSicariiStuff/Tinybra_13B
using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card 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)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Triangle104/Tinybra_13B-Q6_K-GGUF --hf-file tinybra_13b-q6_k.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Tinybra_13B-Q6_K-GGUF --hf-file tinybra_13b-q6_k.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps 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-Q6_K-GGUF --hf-file tinybra_13b-q6_k.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Tinybra_13B-Q6_K-GGUF --hf-file tinybra_13b-q6_k.gguf -c 2048