metadata
language:
- en
license: apache-2.0
base_model: kevin009/lamatama
tags:
- TensorBlock
- GGUF
model-index:
- name: lamatama
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: 36.35
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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: 61.12
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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: 24.72
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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: 37.67
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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: 60.77
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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: 2.27
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
name: Open LLM Leaderboard
kevin009/lamatama - GGUF
This repo contains GGUF format model files for kevin009/lamatama.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
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Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| lamatama-Q2_K.gguf | Q2_K | 0.432 GB | smallest, significant quality loss - not recommended for most purposes |
| lamatama-Q3_K_S.gguf | Q3_K_S | 0.499 GB | very small, high quality loss |
| lamatama-Q3_K_M.gguf | Q3_K_M | 0.548 GB | very small, high quality loss |
| lamatama-Q3_K_L.gguf | Q3_K_L | 0.592 GB | small, substantial quality loss |
| lamatama-Q4_0.gguf | Q4_0 | 0.637 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| lamatama-Q4_K_S.gguf | Q4_K_S | 0.640 GB | small, greater quality loss |
| lamatama-Q4_K_M.gguf | Q4_K_M | 0.668 GB | medium, balanced quality - recommended |
| lamatama-Q5_0.gguf | Q5_0 | 0.766 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| lamatama-Q5_K_S.gguf | Q5_K_S | 0.766 GB | large, low quality loss - recommended |
| lamatama-Q5_K_M.gguf | Q5_K_M | 0.782 GB | large, very low quality loss - recommended |
| lamatama-Q6_K.gguf | Q6_K | 0.903 GB | very large, extremely low quality loss |
| lamatama-Q8_0.gguf | Q8_0 | 1.170 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/lamatama-GGUF --include "lamatama-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/lamatama-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

