metadata
language:
- en
license: llama3
library_name: transformers
tags:
- axolotl
- finetune
- dpo
- facebook
- meta
- pytorch
- llama
- llama-3
- chatml
- TensorBlock
- GGUF
base_model: MaziyarPanahi/calme-2.3-llama3-70b
datasets:
- MaziyarPanahi/truthy-dpo-v0.1-axolotl
pipeline_tag: text-generation
license_name: llama3
license_link: LICENSE
inference: false
model_creator: MaziyarPanahi
quantized_by: MaziyarPanahi
model-index:
- name: calme-2.3-llama3-70b
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: 72.35
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b
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: 86
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b
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: 80.47
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b
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: 63.45
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b
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: 82.95
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b
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: 87.19
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/calme-2.3-llama3-70b
name: Open LLM Leaderboard
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
MaziyarPanahi/calme-2.3-llama3-70b - GGUF
This repo contains GGUF format model files for MaziyarPanahi/calme-2.3-llama3-70b.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
calme-2.3-llama3-70b-Q2_K.gguf | Q2_K | 26.375 GB | smallest, significant quality loss - not recommended for most purposes |
calme-2.3-llama3-70b-Q3_K_S.gguf | Q3_K_S | 30.912 GB | very small, high quality loss |
calme-2.3-llama3-70b-Q3_K_M.gguf | Q3_K_M | 34.268 GB | very small, high quality loss |
calme-2.3-llama3-70b-Q3_K_L.gguf | Q3_K_L | 37.141 GB | small, substantial quality loss |
calme-2.3-llama3-70b-Q4_0.gguf | Q4_0 | 39.970 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
calme-2.3-llama3-70b-Q4_K_S.gguf | Q4_K_S | 40.347 GB | small, greater quality loss |
calme-2.3-llama3-70b-Q4_K_M.gguf | Q4_K_M | 42.520 GB | medium, balanced quality - recommended |
calme-2.3-llama3-70b-Q5_0.gguf | Q5_0 | 48.657 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
calme-2.3-llama3-70b-Q5_K_S.gguf | Q5_K_S | 48.657 GB | large, low quality loss - recommended |
calme-2.3-llama3-70b-Q5_K_M.gguf | Q5_K_M | 49.950 GB | large, very low quality loss - recommended |
calme-2.3-llama3-70b-Q8_0 | Q6_K | 74.975 GB | very large, extremely low quality loss |
calme-2.3-llama3-70b-Q6_K | Q8_0 | 57.888 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/calme-2.3-llama3-70b-GGUF --include "calme-2.3-llama3-70b-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/calme-2.3-llama3-70b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'