metadata
language:
- en
license: apache-2.0
tags:
- text-generation
datasets:
- THUDM/webglm-qa
- databricks/databricks-dolly-15k
- cognitivecomputations/wizard_vicuna_70k_unfiltered
- totally-not-an-llm/EverythingLM-data-V3
- Amod/mental_health_counseling_conversations
- sablo/oasst2_curated
- starfishmedical/webGPT_x_dolly
- Open-Orca/OpenOrca
- mlabonne/chatml_dpo_pairs
base_model: JackFram/llama-68m
widget:
- messages:
- role: system
content: >-
You are a career counselor. The user will provide you with an
individual looking for guidance in their professional life, and your
task is to assist them in determining what careers they are most
suited for based on their skills, interests, and experience. You
should also conduct research into the various options available,
explain the job market trends in different industries, and advice on
which qualifications would be beneficial for pursuing particular
fields.
- role: user
content: Heya!
- role: assistant
content: Hi! How may I help you?
- role: user
content: >-
I am interested in developing a career in software engineering. What
would you recommend me to do?
- messages:
- role: system
content: You are a knowledgeable assistant. Help the user as much as you can.
- role: user
content: How to become healthier?
- messages:
- role: system
content: You are a helpful assistant who provides concise responses.
- role: user
content: Hi!
- role: assistant
content: Hello there! How may I help you?
- role: user
content: >-
I need to build a simple website. Where should I start learning about
web development?
- messages:
- role: system
content: >-
You are a very creative assistant. User will give you a task, which
you should complete with all your knowledge.
- role: user
content: >-
Write the background story of an RPG game about wizards and dragons in
a sci-fi world.
inference:
parameters:
max_new_tokens: 64
penalty_alpha: 0.5
top_k: 4
model-index:
- name: Llama-68M-Chat-v1
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: 23.29
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-Chat-v1
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: 28.27
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-Chat-v1
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: 25.18
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-Chat-v1
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: 47.27
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-Chat-v1
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: 54.3
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-Chat-v1
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
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Llama-68M-Chat-v1
name: Open LLM Leaderboard
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 |