metadata
license: apache-2.0
language:
- en
base_model: FuseAI/FuseChat-7B-VaRM
datasets:
- FuseAI/FuseChat-Mixture
pipeline_tag: text-generation
tags:
- mistral
- mixtral
- solar
- model-fusion
- fusechat
- TensorBlock
- GGUF
library_name: transformers
model-index:
- name: FuseChat-7B-VaRM
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: MT-Bench
type: unknown
metrics:
- type: unknown
value: 8.22
name: score
source:
url: https://huggingface.co/spaces/lmsys/mt-bench
- 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: 62.88
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=FuseAI/FuseChat-7B-VaRM
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: 84.25
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=FuseAI/FuseChat-7B-VaRM
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: 63.71
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=FuseAI/FuseChat-7B-VaRM
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: 45.67
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=FuseAI/FuseChat-7B-VaRM
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: 79.16
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=FuseAI/FuseChat-7B-VaRM
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: 63.46
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=FuseAI/FuseChat-7B-VaRM
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
FuseAI/FuseChat-7B-VaRM - GGUF
This repo contains GGUF format model files for FuseAI/FuseChat-7B-VaRM.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
<s>GPT4 Correct System: {system_prompt}<|end_of_turn|>GPT4 Correct User: {prompt}<|end_of_turn|>GPT4 Correct Assistant:
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
FuseChat-7B-VaRM-Q2_K.gguf | Q2_K | 2.719 GB | smallest, significant quality loss - not recommended for most purposes |
FuseChat-7B-VaRM-Q3_K_S.gguf | Q3_K_S | 3.165 GB | very small, high quality loss |
FuseChat-7B-VaRM-Q3_K_M.gguf | Q3_K_M | 3.519 GB | very small, high quality loss |
FuseChat-7B-VaRM-Q3_K_L.gguf | Q3_K_L | 3.822 GB | small, substantial quality loss |
FuseChat-7B-VaRM-Q4_0.gguf | Q4_0 | 4.109 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
FuseChat-7B-VaRM-Q4_K_S.gguf | Q4_K_S | 4.140 GB | small, greater quality loss |
FuseChat-7B-VaRM-Q4_K_M.gguf | Q4_K_M | 4.368 GB | medium, balanced quality - recommended |
FuseChat-7B-VaRM-Q5_0.gguf | Q5_0 | 4.998 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
FuseChat-7B-VaRM-Q5_K_S.gguf | Q5_K_S | 4.998 GB | large, low quality loss - recommended |
FuseChat-7B-VaRM-Q5_K_M.gguf | Q5_K_M | 5.131 GB | large, very low quality loss - recommended |
FuseChat-7B-VaRM-Q6_K.gguf | Q6_K | 5.942 GB | very large, extremely low quality loss |
FuseChat-7B-VaRM-Q8_0.gguf | Q8_0 | 7.696 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/FuseChat-7B-VaRM-GGUF --include "FuseChat-7B-VaRM-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/FuseChat-7B-VaRM-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'