metadata
language:
- en
license: mit
library_name: transformers
inference:
parameters:
max_new_tokens: 64
do_sample: true
temperature: 0.1
repetition_penalty: 10
no_repeat_ngram_size: 4
eta_cutoff: 0.0006
renormalize_logits: true
widget:
- text: My name is El Microondas the Wise, and
example_title: El Microondas
- text: Kennesaw State University is a public
example_title: Kennesaw State University
- text: >-
Bungie Studios is an American video game developer. They are most famous
for developing the award winning Halo series of video games. They also
made Destiny. The studio was founded
example_title: Bungie
- text: The Mona Lisa is a world-renowned painting created by
example_title: Mona Lisa
- text: >-
The Harry Potter series, written by J.K. Rowling, begins with the book
titled
example_title: Harry Potter Series
- text: >-
Question: I have cities, but no houses. I have mountains, but no trees. I
have water, but no fish. What am I?
Answer:
example_title: Riddle
- text: The process of photosynthesis involves the conversion of
example_title: Photosynthesis
- text: >-
Jane went to the store to buy some groceries. She picked up apples,
oranges, and a loaf of bread. When she got home, she realized she forgot
example_title: Story Continuation
- text: >-
Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph,
and another train leaves Station B at 10:00 AM and travels at 80 mph, when
will they meet if the distance between the stations is 300 miles?
To determine
example_title: Math Problem
- text: In the context of computer programming, an algorithm is
example_title: Algorithm Definition
pipeline_tag: text-generation
datasets:
- kenhktsui/minipile_quality_score_v1
- kenhktsui/simple_wikipedia_LM_quality_score_v1
- kenhktsui/refinedweb-3m_quality_score_v1
- kenhktsui/TM-DATA_quality_score_v1
- kenhktsui/openwebtext_quality_score_v1
tags:
- TensorBlock
- GGUF
base_model: kenhktsui/nano-phi-115M-v0.1
model-index:
- name: nano-phi-115M-v0.1
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: 21.93
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1
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: 27.86
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1
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: 25.34
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1
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: 46
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1
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: 50.83
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1
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=kenhktsui/nano-phi-115M-v0.1
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
kenhktsui/nano-phi-115M-v0.1 - GGUF
This repo contains GGUF format model files for kenhktsui/nano-phi-115M-v0.1.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| nano-phi-115M-v0.1-Q2_K.gguf | Q2_K | 0.061 GB | smallest, significant quality loss - not recommended for most purposes |
| nano-phi-115M-v0.1-Q3_K_S.gguf | Q3_K_S | 0.067 GB | very small, high quality loss |
| nano-phi-115M-v0.1-Q3_K_M.gguf | Q3_K_M | 0.069 GB | very small, high quality loss |
| nano-phi-115M-v0.1-Q3_K_L.gguf | Q3_K_L | 0.072 GB | small, substantial quality loss |
| nano-phi-115M-v0.1-Q4_0.gguf | Q4_0 | 0.077 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| nano-phi-115M-v0.1-Q4_K_S.gguf | Q4_K_S | 0.077 GB | small, greater quality loss |
| nano-phi-115M-v0.1-Q4_K_M.gguf | Q4_K_M | 0.078 GB | medium, balanced quality - recommended |
| nano-phi-115M-v0.1-Q5_0.gguf | Q5_0 | 0.086 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| nano-phi-115M-v0.1-Q5_K_S.gguf | Q5_K_S | 0.086 GB | large, low quality loss - recommended |
| nano-phi-115M-v0.1-Q5_K_M.gguf | Q5_K_M | 0.087 GB | large, very low quality loss - recommended |
| nano-phi-115M-v0.1-Q6_K.gguf | Q6_K | 0.096 GB | very large, extremely low quality loss |
| nano-phi-115M-v0.1-Q8_0.gguf | Q8_0 | 0.124 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/nano-phi-115M-v0.1-GGUF --include "nano-phi-115M-v0.1-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/nano-phi-115M-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'