Trained Models 🏋️
Collection
They may be small, but they're training like giants!
•
8 items
•
Updated
•
16
A Llama Chat Model of 68M Parameters
- Base model: JackFram/llama-68m
- Datasets:
- Availability in other ML formats:
Recommended Prompt Format
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
Recommended Inference Parameters
penalty_alpha: 0.5
top_k: 4
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 29.72 |
| AI2 Reasoning Challenge (25-Shot) | 23.29 |
| HellaSwag (10-Shot) | 28.27 |
| MMLU (5-Shot) | 25.18 |
| TruthfulQA (0-shot) | 47.27 |
| Winogrande (5-shot) | 54.30 |
| GSM8k (5-shot) | 0.00 |
- Downloads last month
- 3,722
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for Felladrin/Llama-68M-Chat-v1
Datasets used to train Felladrin/Llama-68M-Chat-v1
Spaces using Felladrin/Llama-68M-Chat-v1 2
Collection including Felladrin/Llama-68M-Chat-v1
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard23.290
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard28.270
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard25.180
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard47.270
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard54.300
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard0.000