metadata
language:
- en
- de
- fr
- it
- pt
- hi
- es
- th
license: llama3.1
library_name: transformers
tags:
- reflection
- unsloth
- peft
- llama
- TensorBlock
- GGUF
base_model: leafspark/Llama-3.1-8B-MultiReflection-Instruct
datasets:
- leafspark/DetailedReflection-Claude-v3_5-Sonnet
metrics:
- accuracy
pipeline_tag: text-generation
model-index:
- name: Llama-3.1-8B-MultiReflection-Instruct
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 71.25
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=leafspark/Llama-3.1-8B-MultiReflection-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 28.45
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=leafspark/Llama-3.1-8B-MultiReflection-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 12.54
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=leafspark/Llama-3.1-8B-MultiReflection-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 5.7
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=leafspark/Llama-3.1-8B-MultiReflection-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 8.52
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=leafspark/Llama-3.1-8B-MultiReflection-Instruct
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 30.27
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=leafspark/Llama-3.1-8B-MultiReflection-Instruct
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
leafspark/Llama-3.1-8B-MultiReflection-Instruct - GGUF
This repo contains GGUF format model files for leafspark/Llama-3.1-8B-MultiReflection-Instruct.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Llama-3.1-8B-MultiReflection-Instruct-Q2_K.gguf | Q2_K | 2.961 GB | smallest, significant quality loss - not recommended for most purposes |
| Llama-3.1-8B-MultiReflection-Instruct-Q3_K_S.gguf | Q3_K_S | 3.413 GB | very small, high quality loss |
| Llama-3.1-8B-MultiReflection-Instruct-Q3_K_M.gguf | Q3_K_M | 3.743 GB | very small, high quality loss |
| Llama-3.1-8B-MultiReflection-Instruct-Q3_K_L.gguf | Q3_K_L | 4.025 GB | small, substantial quality loss |
| Llama-3.1-8B-MultiReflection-Instruct-Q4_0.gguf | Q4_0 | 4.341 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Llama-3.1-8B-MultiReflection-Instruct-Q4_K_S.gguf | Q4_K_S | 4.370 GB | small, greater quality loss |
| Llama-3.1-8B-MultiReflection-Instruct-Q4_K_M.gguf | Q4_K_M | 4.583 GB | medium, balanced quality - recommended |
| Llama-3.1-8B-MultiReflection-Instruct-Q5_0.gguf | Q5_0 | 5.215 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Llama-3.1-8B-MultiReflection-Instruct-Q5_K_S.gguf | Q5_K_S | 5.215 GB | large, low quality loss - recommended |
| Llama-3.1-8B-MultiReflection-Instruct-Q5_K_M.gguf | Q5_K_M | 5.339 GB | large, very low quality loss - recommended |
| Llama-3.1-8B-MultiReflection-Instruct-Q6_K.gguf | Q6_K | 6.143 GB | very large, extremely low quality loss |
| Llama-3.1-8B-MultiReflection-Instruct-Q8_0.gguf | Q8_0 | 7.954 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/Llama-3.1-8B-MultiReflection-Instruct-GGUF --include "Llama-3.1-8B-MultiReflection-Instruct-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/Llama-3.1-8B-MultiReflection-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'