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TomGrc_-_FusionNet_linear-gguf
RichardErkhov/TomGrc_-_FusionNet_linear-gguf
TomGrc_-_FusionNet_linear-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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At a glance
- Access
- Public
- Created
- Aug 30, 2024
- Updated
- Aug 30, 2024
- SHA
- 3f6f9958
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
FusionNet_linear - GGUF
- Model creator: https://huggingface.co/TomGrc/
- Original model: https://huggingface.co/TomGrc/FusionNet_linear/
| Name | Quant method | Size |
|---|---|---|
| FusionNet_linear.Q2_K.gguf | Q2_K | 3.73GB |
| FusionNet_linear.IQ3_XS.gguf | IQ3_XS | 4.14GB |
| FusionNet_linear.IQ3_S.gguf | IQ3_S | 4.37GB |
| FusionNet_linear.Q3_K_S.gguf | Q3_K_S | 4.34GB |
| FusionNet_linear.IQ3_M.gguf | IQ3_M | 4.51GB |
| FusionNet_linear.Q3_K.gguf | Q3_K | 4.84GB |
| FusionNet_linear.Q3_K_M.gguf | Q3_K_M | 4.84GB |
| FusionNet_linear.Q3_K_L.gguf | Q3_K_L | 5.26GB |
| FusionNet_linear.IQ4_XS.gguf | IQ4_XS | 5.43GB |
| FusionNet_linear.Q4_0.gguf | Q4_0 | 5.66GB |
| FusionNet_linear.IQ4_NL.gguf | IQ4_NL | 5.72GB |
| FusionNet_linear.Q4_K_S.gguf | Q4_K_S | 5.7GB |
| FusionNet_linear.Q4_K.gguf | Q4_K | 6.02GB |
| FusionNet_linear.Q4_K_M.gguf | Q4_K_M | 6.02GB |
| FusionNet_linear.Q4_1.gguf | Q4_1 | 6.27GB |
| FusionNet_linear.Q5_0.gguf | Q5_0 | 6.89GB |
| FusionNet_linear.Q5_K_S.gguf | Q5_K_S | 5.89GB |
| FusionNet_linear.Q5_K.gguf | Q5_K | 7.08GB |
| FusionNet_linear.Q5_K_M.gguf | Q5_K_M | 7.08GB |
| FusionNet_linear.Q5_1.gguf | Q5_1 | 7.51GB |
| FusionNet_linear.Q6_K.gguf | Q6_K | 8.2GB |
| FusionNet_linear.Q8_0.gguf | Q8_0 | 10.62GB |
Original model description:
language:
- en license: mit tags:
- merge pipeline_tag: text-generation model-index:
- name: FusionNet_linear
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: 71.25 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_linear 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: 88.44 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_linear 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: 66.35 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_linear 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: 71.94 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_linear 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: 83.27 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_linear 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: 65.35 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_linear 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:
FusionNet_linear
Fine-tuned model on English language using linear Fusion method.
Model description
This is an experiment with the linear Fusion method of FusionNet. This model has 10.7B parameters, and this model is fine-tuned. Enjoy!
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 74.43 |
| AI2 Reasoning Challenge (25-Shot) | 71.25 |
| HellaSwag (10-Shot) | 88.44 |
| MMLU (5-Shot) | 66.35 |
| TruthfulQA (0-shot) | 71.94 |
| Winogrande (5-shot) | 83.27 |
| GSM8k (5-shot) | 65.35 |
- Created
- Aug 30, 2024
- Updated
- Aug 30, 2024