metadata
language:
- en
- it
license: llama3
library_name: transformers
tags:
- facebook
- meta
- pythorch
- llama
- llama-3
- llamantino
- TensorBlock
- GGUF
base_model: swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
datasets:
- gsarti/clean_mc4_it
- Chat-Error/wizard_alpaca_dolly_orca
- mlabonne/orpo-dpo-mix-40k
metrics:
- accuracy
model_creator: Marco Polignano - SWAP Research Group
pipeline_tag: text-generation
model-index:
- name: LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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: 74.57
name: normalized accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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: 92.75
name: normalized accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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: 66.85
name: accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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: 75.93
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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: 82
name: accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
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: 58.61
name: accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA - GGUF
This repo contains GGUF format model files for swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA.
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|>
{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 |
|---|---|---|---|
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q2_K.gguf | Q2_K | 2.961 GB | smallest, significant quality loss - not recommended for most purposes |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q3_K_S.gguf | Q3_K_S | 3.413 GB | very small, high quality loss |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q3_K_M.gguf | Q3_K_M | 3.743 GB | very small, high quality loss |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q3_K_L.gguf | Q3_K_L | 4.025 GB | small, substantial quality loss |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q4_0.gguf | Q4_0 | 4.341 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q4_K_S.gguf | Q4_K_S | 4.370 GB | small, greater quality loss |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q4_K_M.gguf | Q4_K_M | 4.583 GB | medium, balanced quality - recommended |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q5_0.gguf | Q5_0 | 5.215 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q5_K_S.gguf | Q5_K_S | 5.215 GB | large, low quality loss - recommended |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q5_K_M.gguf | Q5_K_M | 5.339 GB | large, very low quality loss - recommended |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-Q6_K.gguf | Q6_K | 6.143 GB | very large, extremely low quality loss |
| LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-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/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-GGUF --include "LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-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/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'