ModelHub XC b76fc2de0e 初始化项目,由ModelHub XC社区提供模型
Model: Locutusque/llama-3-neural-chat-v1-8b
Source: Original Platform
2026-05-12 02:17:33 +08:00

license, library_name, base_model, datasets, model-index
license library_name base_model datasets model-index
other transformers meta-llama/Meta-Llama-3-8B
mlabonne/orpo-dpo-mix-40k
Open-Orca/SlimOrca-Dedup
jondurbin/airoboros-3.2
microsoft/orca-math-word-problems-200k
m-a-p/Code-Feedback
MaziyarPanahi/WizardLM_evol_instruct_V2_196k
name results
llama-3-neural-chat-v1-8b
task dataset metrics source
type name
text-generation Text Generation
name type config split args
AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test
num_few_shot
25
type value name
acc_norm 60.84 normalized accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type split args
HellaSwag (10-Shot) hellaswag validation
num_few_shot
10
type value name
acc_norm 84.13 normalized accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
MMLU (5-Shot) cais/mmlu all test
num_few_shot
5
type value name
acc 64.69 accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
TruthfulQA (0-shot) truthful_qa multiple_choice validation
num_few_shot
0
type value
mc2 56.34
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
Winogrande (5-shot) winogrande winogrande_xl validation
num_few_shot
5
type value name
acc 78.22 accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
GSM8k (5-shot) gsm8k main test
num_few_shot
5
type value name
acc 54.81 accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/llama-3-neural-chat-v1-8b Open LLM Leaderboard

llama-3-neural-chat-v1-8b

image/png

Model Details

Model Description

I fine-tuned llama-3 8B on an approach similar to Intel's neural chat language model. I have slightly modified the data sources so it is stronger in coding, math, and writing. I use both SFT and DPO.

Quants

EXL2 @bartowski

GGUF @bartowski

Uses

This model has great performance in writing and coding.

Training Data

  • Open-Orca/SlimOrca-Dedup
  • jondurbin/airoboros-3.2
  • microsoft/orca-math-word-problems-200k
  • m-a-p/Code-Feedback
  • MaziyarPanahi/WizardLM_evol_instruct_V2_196k
  • mlabonne/orpo-dpo-mix-40k

Direct Use

Conversational AI.

Evaluations

Tasks Version Filter n-shot Metric Value Stderr
truthfulqa_mc2 2 none 0 acc 0.5627 ± 0.0154
gsm8k 3 strict-match 5 exact_match 0.5481 ± 0.0137
flexible-extract 5 exact_match 0.5557 ± 0.0137
agieval_nous N/A none 0 acc 0.3763 ± 0.0093
none 0 acc_norm 0.3665 ± 0.0093
- agieval_aqua_rat 1 none 0 acc 0.2087 ± 0.0255
none 0 acc_norm 0.2047 ± 0.0254
- agieval_logiqa_en 1 none 0 acc 0.3456 ± 0.0187
none 0 acc_norm 0.3594 ± 0.0188
- agieval_lsat_ar 1 none 0 acc 0.1826 ± 0.0255
none 0 acc_norm 0.1783 ± 0.0253
- agieval_lsat_lr 1 none 0 acc 0.3549 ± 0.0212
none 0 acc_norm 0.3451 ± 0.0211
- agieval_lsat_rc 1 none 0 acc 0.5242 ± 0.0305
none 0 acc_norm 0.5130 ± 0.0305
- agieval_sat_en 1 none 0 acc 0.6650 ± 0.0330
none 0 acc_norm 0.6505 ± 0.0333
- agieval_sat_en_without_passage 1 none 0 acc 0.4175 ± 0.0344
none 0 acc_norm 0.3738 ± 0.0338
- agieval_sat_math 1 none 0 acc 0.4227 ± 0.0334
none 0 acc_norm 0.3682 ± 0.0326

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 66.50
AI2 Reasoning Challenge (25-Shot) 60.84
HellaSwag (10-Shot) 84.13
MMLU (5-Shot) 64.69
TruthfulQA (0-shot) 56.34
Winogrande (5-shot) 78.22
GSM8k (5-shot) 54.81
Description
Model synced from source: Locutusque/llama-3-neural-chat-v1-8b
Readme 2.6 MiB