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OEvortex_-_HelpingAI-110M-gguf
RichardErkhov/OEvortex_-_HelpingAI-110M-gguf
OEvortex_-_HelpingAI-110M-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf1.6 GB · 100%
At a glance
- Access
- Public
- Created
- Jul 3, 2024
- Updated
- Jul 3, 2024
- SHA
- 4d256ec0
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
HelpingAI-110M - GGUF
- Model creator: https://huggingface.co/OEvortex/
- Original model: https://huggingface.co/OEvortex/HelpingAI-110M/
| Name | Quant method | Size |
|---|---|---|
| HelpingAI-110M.Q2_K.gguf | Q2_K | 0.05GB |
| HelpingAI-110M.IQ3_XS.gguf | IQ3_XS | 0.05GB |
| HelpingAI-110M.IQ3_S.gguf | IQ3_S | 0.05GB |
| HelpingAI-110M.Q3_K_S.gguf | Q3_K_S | 0.05GB |
| HelpingAI-110M.IQ3_M.gguf | IQ3_M | 0.06GB |
| HelpingAI-110M.Q3_K.gguf | Q3_K | 0.06GB |
| HelpingAI-110M.Q3_K_M.gguf | Q3_K_M | 0.06GB |
| HelpingAI-110M.Q3_K_L.gguf | Q3_K_L | 0.06GB |
| HelpingAI-110M.IQ4_XS.gguf | IQ4_XS | 0.06GB |
| HelpingAI-110M.Q4_0.gguf | Q4_0 | 0.06GB |
| HelpingAI-110M.IQ4_NL.gguf | IQ4_NL | 0.06GB |
| HelpingAI-110M.Q4_K_S.gguf | Q4_K_S | 0.06GB |
| HelpingAI-110M.Q4_K.gguf | Q4_K | 0.07GB |
| HelpingAI-110M.Q4_K_M.gguf | Q4_K_M | 0.07GB |
| HelpingAI-110M.Q4_1.gguf | Q4_1 | 0.07GB |
| HelpingAI-110M.Q5_0.gguf | Q5_0 | 0.07GB |
| HelpingAI-110M.Q5_K_S.gguf | Q5_K_S | 0.07GB |
| HelpingAI-110M.Q5_K.gguf | Q5_K | 0.08GB |
| HelpingAI-110M.Q5_K_M.gguf | Q5_K_M | 0.08GB |
| HelpingAI-110M.Q5_1.gguf | Q5_1 | 0.08GB |
| HelpingAI-110M.Q6_K.gguf | Q6_K | 0.08GB |
| HelpingAI-110M.Q8_0.gguf | Q8_0 | 0.11GB |
Original model description:
language:
- en license: other library_name: transformers tags:
- Text-Generation
- Transformers
- HelpingAI datasets:
- OEvortex/vortex-mini metrics:
- speed license_name: hsul license_link: https://huggingface.co/OEvortex/vortex-3b/raw/main/LICENSE.md model-index:
- name: HelpingAI-110M
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: 22.78 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/HelpingAI-110M 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: 28.02 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/HelpingAI-110M 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: 23.66 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/HelpingAI-110M 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: 48.25 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/HelpingAI-110M 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: 51.62 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/HelpingAI-110M 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: 0.0 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/HelpingAI-110M name: Open LLM Leaderboard
- 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:
🌟 HelpingAI-110M Model Card 🌟
📊 Datasets used:
- OEvortex/vortex-mini
🗣️ Language:
- English (en)
🔒 License:
HelpingAI Simplified Universal License (HSUL)
🧠 Model Overview: HelpingAI-110M is a very lite version of the HelpingAI model, trained on a 110M parameters.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 29.05 |
| AI2 Reasoning Challenge (25-Shot) | 22.78 |
| HellaSwag (10-Shot) | 28.02 |
| MMLU (5-Shot) | 23.66 |
| TruthfulQA (0-shot) | 48.25 |
| Winogrande (5-shot) | 51.62 |
| GSM8k (5-shot) | 0.00 |
- Created
- Jul 3, 2024
- Updated
- Jul 3, 2024