---
language:
- en
license: llama3
library_name: transformers
pipeline_tag: text2text-generation
model-index:
- name: Al_Dente_v1_8b
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 36.94
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 27.25
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 3.02
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 6.6
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 8.27
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 20.67
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=pankajmathur/Al_Dente_v1_8b
name: Open LLM Leaderboard
---
**Model Name: Llama 3 Al_Dente_v1_8b**
# Llama 3 Al_Dente_v1_8b is trained on various SFT Datasets
Passionate about Generative AI? I help companies to privately train and deploy custom LLM/MLLM affordably. For startups, I can even assist with securing GPU grants to get you started. Let's chat!
https://www.linkedin.com/in/pankajam Looking forward to connecting!
### NOTICE
By providing proper credit and attribution, you are granted permission to use this model as a foundational base for further Full fine tuning, DPO, PPO or ORPO tuning and any kind of Merges.
I actively encourage users to customize and enhance the model according to their specific needs, as this version is designed to be a comprehensive general model.
Dive in and innovate!
### Evaluation
Coming Soon..
### Example Usage
Here is the ChatML prompt format
```
<|im_start|>system
You are Al Dente, a helpful AI assistant.<|im_end|>
<|im_start|>user
Hello Al Dente, what can you do for me?<|im_end|>
<|im_start|>assistant
```
Below shows a code example on how to use this model
```python
from transformers import AutoModel, AutoTokenizer
model_slug = "pankajmathur/Al_Dente_v1_8b"
model = AutoModel.from_pretrained(model_slug)
tokenizer = AutoTokenizer.from_pretrained(model_slug)
messages = [
{"role": "system", "content": "You are Al Dente, a helpful AI assistant."},
{"role": "user", "content": "Hello Al Dente, what can you do for me?"}
]
gen_input = tokenizer.apply_chat_template(messages, return_tensors="pt")
model.generate(**gen_input)
```
This model is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE)
**Quants**
GGUF : Coming Soon
AWQ: Coming Soon
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_pankajmathur__Al_Dente_v1_8b)
| Metric |Value|
|-------------------|----:|
|Avg. |17.12|
|IFEval (0-Shot) |36.94|
|BBH (3-Shot) |27.25|
|MATH Lvl 5 (4-Shot)| 3.02|
|GPQA (0-shot) | 6.60|
|MuSR (0-shot) | 8.27|
|MMLU-PRO (5-shot) |20.67|