metadata
language:
- en
license: apache-2.0
library_name: transformers
datasets:
- togethercomputer/RedPajama-Data-1T
- databricks/databricks-dolly-15k
- OpenAssistant/oasst1
- Muennighoff/natural-instructions
- Muennighoff/P3
pipeline_tag: text-generation
tags:
- TensorBlock
- GGUF
base_model: acrastt/RedPajama-INCITE-Chat-Instruct-3B-V1
model-index:
- name: RedPajama-INCITE-Chat-Instruct-3B-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: 42.58
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/RedPajama-INCITE-Chat-Instruct-3B-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: 67.48
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/RedPajama-INCITE-Chat-Instruct-3B-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: 25.99
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/RedPajama-INCITE-Chat-Instruct-3B-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: 33.62
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/RedPajama-INCITE-Chat-Instruct-3B-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: 64.8
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/RedPajama-INCITE-Chat-Instruct-3B-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: 0.91
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=acrastt/RedPajama-INCITE-Chat-Instruct-3B-V1
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
acrastt/RedPajama-INCITE-Chat-Instruct-3B-V1 - GGUF
This repo contains GGUF format model files for acrastt/RedPajama-INCITE-Chat-Instruct-3B-V1.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
RedPajama-INCITE-Chat-Instruct-3B-V1-Q2_K.gguf | Q2_K | 1.012 GB | smallest, significant quality loss - not recommended for most purposes |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q3_K_S.gguf | Q3_K_S | 1.163 GB | very small, high quality loss |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q3_K_M.gguf | Q3_K_M | 1.377 GB | very small, high quality loss |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q3_K_L.gguf | Q3_K_L | 1.493 GB | small, substantial quality loss |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q4_0.gguf | Q4_0 | 1.490 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q4_K_S.gguf | Q4_K_S | 1.502 GB | small, greater quality loss |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q4_K_M.gguf | Q4_K_M | 1.664 GB | medium, balanced quality - recommended |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q5_0.gguf | Q5_0 | 1.798 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q5_K_S.gguf | Q5_K_S | 1.798 GB | large, low quality loss - recommended |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q5_K_M.gguf | Q5_K_M | 1.928 GB | large, very low quality loss - recommended |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q6_K.gguf | Q6_K | 2.126 GB | very large, extremely low quality loss |
RedPajama-INCITE-Chat-Instruct-3B-V1-Q8_0.gguf | Q8_0 | 2.751 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/RedPajama-INCITE-Chat-Instruct-3B-V1-GGUF --include "RedPajama-INCITE-Chat-Instruct-3B-V1-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/RedPajama-INCITE-Chat-Instruct-3B-V1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'