Instructions to use ClaudioItaly/Albacus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClaudioItaly/Albacus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ClaudioItaly/Albacus")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ClaudioItaly/Albacus") model = AutoModelForCausalLM.from_pretrained("ClaudioItaly/Albacus") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ClaudioItaly/Albacus with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ClaudioItaly/Albacus" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ClaudioItaly/Albacus", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ClaudioItaly/Albacus
- SGLang
How to use ClaudioItaly/Albacus with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "ClaudioItaly/Albacus" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ClaudioItaly/Albacus", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "ClaudioItaly/Albacus" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ClaudioItaly/Albacus", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ClaudioItaly/Albacus with Docker Model Runner:
docker model run hf.co/ClaudioItaly/Albacus
metadata
license: mit
library_name: transformers
tags:
- mergekit
- merge
base_model:
- ClaudioItaly/Evolutionstory-7B-v2.2
model-index:
- name: Albacus
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 46.67
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/Albacus
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 31.64
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/Albacus
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 6.42
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/Albacus
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 2.91
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/Albacus
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 10.66
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/Albacus
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 24.05
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/Albacus
name: Open LLM Leaderboard
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the passthrough merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 0
- 4
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 3
- 4
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 4
- 8
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 7
- 8
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 8
- 12
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 11
- 12
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 12
- 16
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 15
- 16
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 16
- 20
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 19
- 20
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 20
- 24
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 23
- 24
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 24
- 28
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 27
- 28
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 28
- 32
- sources:
- model: ClaudioItaly/Evolutionstory-7B-v2.2
layer_range:
- 31
- 32
parameters:
scale:
- filter: o_proj
value: 0
- filter: down_proj
value: 0
- value: 1
merge_method: passthrough
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 20.39 |
| IFEval (0-Shot) | 46.67 |
| BBH (3-Shot) | 31.64 |
| MATH Lvl 5 (4-Shot) | 6.42 |
| GPQA (0-shot) | 2.91 |
| MuSR (0-shot) | 10.66 |
| MMLU-PRO (5-shot) | 24.05 |