Instructions to use appvoid/dot-v1.8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use appvoid/dot-v1.8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/dot-v1.8")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("appvoid/dot-v1.8") model = AutoModelForCausalLM.from_pretrained("appvoid/dot-v1.8") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use appvoid/dot-v1.8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "appvoid/dot-v1.8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/dot-v1.8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/appvoid/dot-v1.8
- SGLang
How to use appvoid/dot-v1.8 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 "appvoid/dot-v1.8" \ --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": "appvoid/dot-v1.8", "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 "appvoid/dot-v1.8" \ --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": "appvoid/dot-v1.8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use appvoid/dot-v1.8 with Docker Model Runner:
docker model run hf.co/appvoid/dot-v1.8
metadata
base_model:
- sreeramajay/TinyLlama-1.1B-orca-v1.0
- AIGym/TinyLlama-1.1B-2.5T-chat-and-function-calling
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
- vihangd/DopeyTinyLlama-1.1B-v1
- ShieldX/manovyadh-1.1B-v1-chat
- appvoid/palmer-003
- TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
- raidhon/coven_tiny_1.1b_32k_orpo_alpha
- l3utterfly/tinyllama-1.1b-layla-v4
library_name: transformers
tags:
- mergekit
- merge
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the task arithmetic merge method using TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T as a base.
Models Merged
The following models were included in the merge:
- sreeramajay/TinyLlama-1.1B-orca-v1.0
- AIGym/TinyLlama-1.1B-2.5T-chat-and-function-calling
- TinyLlama/TinyLlama-1.1B-Chat-v1.0
- vihangd/DopeyTinyLlama-1.1B-v1
- ShieldX/manovyadh-1.1B-v1-chat
- appvoid/palmer-003
- raidhon/coven_tiny_1.1b_32k_orpo_alpha
- l3utterfly/tinyllama-1.1b-layla-v4
Configuration
The following YAML configuration was used to produce this model:
models:
- model: vihangd/DopeyTinyLlama-1.1B-v1
parameters:
density: 0.20
weight: 0.30
- model: raidhon/coven_tiny_1.1b_32k_orpo_alpha
parameters:
density: 0.45
weight: 0.26
- model: l3utterfly/tinyllama-1.1b-layla-v4
parameters:
density: 0.25
weight: 0.125
- model: ShieldX/manovyadh-1.1B-v1-chat
parameters:
density: 0.18
weight: 0.125
- model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
parameters:
density: 0.25
weight: 0.25
- model: sreeramajay/TinyLlama-1.1B-orca-v1.0
parameters:
density: 0.15
weight: 0.37
- model: AIGym/TinyLlama-1.1B-2.5T-chat-and-function-calling
parameters:
density: 0.25
weight: 0.26
- model: appvoid/palmer-003
parameters:
density: 0.75
weight: 0.50
merge_method: task_arithmetic
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
parameters:
normalize: false
int8_mask: true
dtype: float16