Instructions to use LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive with Adapters:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("undefined")
model.load_adapter("LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive", set_active=True)

Transformers

How to use LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive")
model = AutoModelForCausalLM.from_pretrained("LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive

SGLang

How to use LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive 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 "LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive",
    max_seq_length=2048,
)

Docker Model Runner
How to use LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive with Docker Model Runner:
```
docker model run hf.co/LeroyDyer/_Spydaz_Web_LCARS_AdvancedHuman_Archive
```

README.md

by Wijaya01 - opened about 10 hours ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+98

-99

Files changed (1) hide show

README.md +98 -99

README.md CHANGED Viewed

@@ -4,110 +4,109 @@ base_model:
 - LeroyDyer/_Spydaz_Web_AGI_DeepThinker_LCARS_
 - LeroyDyer/_Spydaz_Web_ONTOLOGY_OFFICER_
 metrics:
-  - accuracy
-  - bertscore
-  - bleu
-  - brier_score
-  - cer
-  - character
-  - charcut_mt
-  - chrf
-  - code_eval
 tags:
-  - text-generation-inference
-  - transformers
-  - unsloth
-  - mistral
-  - trl
-  - chemistry
-  - biology
-  - legal
-  - art
-  - music
-  - finance
-  - code
-  - medical
-  - merge
-  - climate
-  - chain-of-thought
-  - tree-of-knowledge
-  - forest-of-thoughts
-  - visual-spacial-sketchpad
-  - alpha-mind
-  - knowledge-graph
-  - entity-detection
-  - encyclopedia
-  - wikipedia
-  - stack-exchange
-  - Reddit
-  - Cyber-series
-  - MegaMind
-  - Cybertron
-  - SpydazWeb
-  - Spydaz
-  - LCARS
-  - star-trek
-  - mega-transformers
-  - Mulit-Mega-Merge
-  - Multi-Lingual
-  - Afro-Centric
-  - African-Model
-  - Ancient-One
 license: apache-2.0
 language:
-  - en
-  - sw
-  - ig
-  - so
-  - es
-  - ca
 datasets:
-  - gretelai/synthetic_text_to_sql
-  - HuggingFaceTB/cosmopedia
-  - teknium/OpenHermes-2.5
-  - Open-Orca/SlimOrca
-  - Open-Orca/OpenOrca
-  - cognitivecomputations/dolphin-coder
-  - databricks/databricks-dolly-15k
-  - yahma/alpaca-cleaned
-  - uonlp/CulturaX
-  - mwitiderrick/SwahiliPlatypus
-  - swahili
-  - Rogendo/English-Swahili-Sentence-Pairs
-  - ise-uiuc/Magicoder-Evol-Instruct-110K
-  - meta-math/MetaMathQA
-  - abacusai/ARC_DPO_FewShot
-  - abacusai/MetaMath_DPO_FewShot
-  - abacusai/HellaSwag_DPO_FewShot
-  - HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset
-  - HuggingFaceFW/fineweb
-  - occiglot/occiglot-fineweb-v0.5
-  - omi-health/medical-dialogue-to-soap-summary
-  - keivalya/MedQuad-MedicalQnADataset
-  - ruslanmv/ai-medical-dataset
-  - Shekswess/medical_llama3_instruct_dataset_short
-  - ShenRuililin/MedicalQnA
-  - virattt/financial-qa-10K
-  - PatronusAI/financebench
-  - takala/financial_phrasebank
-  - Replete-AI/code_bagel
-  - athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
-  - IlyaGusev/gpt_roleplay_realm
-  - rickRossie/bluemoon_roleplay_chat_data_300k_messages
-  - jtatman/hypnosis_dataset
-  - Hypersniper/philosophy_dialogue
-  - Locutusque/function-calling-chatml
-  - bible-nlp/biblenlp-corpus
-  - DatadudeDev/Bible
-  - Helsinki-NLP/bible_para
-  - HausaNLP/AfriSenti-Twitter
-  - aixsatoshi/Chat-with-cosmopedia
-  - HuggingFaceTB/cosmopedia-100k
-  - HuggingFaceFW/fineweb-edu
-  - m-a-p/CodeFeedback-Filtered-Instruction
-  - heliosbrahma/mental_health_chatbot_dataset
 pipeline_tag: text-generation
-library_name: adapter-transformers
 ---

 - LeroyDyer/_Spydaz_Web_AGI_DeepThinker_LCARS_
 - LeroyDyer/_Spydaz_Web_ONTOLOGY_OFFICER_
 metrics:
+- accuracy
+- bertscore
+- bleu
+- brier_score
+- cer
+- character
+- charcut_mt
+- chrf
+- code_eval
 tags:
+- text-generation-inference
+- transformers
+- unsloth
+- mistral
+- trl
+- chemistry
+- biology
+- legal
+- art
+- music
+- finance
+- code
+- medical
+- merge
+- climate
+- chain-of-thought
+- tree-of-knowledge
+- forest-of-thoughts
+- visual-spacial-sketchpad
+- alpha-mind
+- knowledge-graph
+- entity-detection
+- encyclopedia
+- wikipedia
+- stack-exchange
+- Reddit
+- Cyber-series
+- MegaMind
+- Cybertron
+- SpydazWeb
+- Spydaz
+- LCARS
+- star-trek
+- mega-transformers
+- Mulit-Mega-Merge
+- Multi-Lingual
+- Afro-Centric
+- African-Model
+- Ancient-One
 license: apache-2.0
 language:
+- en
+- sw
+- ig
+- so
+- es
+- ca
 datasets:
+- gretelai/synthetic_text_to_sql
+- HuggingFaceTB/cosmopedia
+- teknium/OpenHermes-2.5
+- Open-Orca/SlimOrca
+- Open-Orca/OpenOrca
+- cognitivecomputations/dolphin-coder
+- databricks/databricks-dolly-15k
+- yahma/alpaca-cleaned
+- uonlp/CulturaX
+- mwitiderrick/SwahiliPlatypus
+- swahili
+- Rogendo/English-Swahili-Sentence-Pairs
+- ise-uiuc/Magicoder-Evol-Instruct-110K
+- meta-math/MetaMathQA
+- abacusai/ARC_DPO_FewShot
+- abacusai/MetaMath_DPO_FewShot
+- abacusai/HellaSwag_DPO_FewShot
+- HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset
+- HuggingFaceFW/fineweb
+- occiglot/occiglot-fineweb-v0.5
+- omi-health/medical-dialogue-to-soap-summary
+- keivalya/MedQuad-MedicalQnADataset
+- ruslanmv/ai-medical-dataset
+- Shekswess/medical_llama3_instruct_dataset_short
+- ShenRuililin/MedicalQnA
+- virattt/financial-qa-10K
+- PatronusAI/financebench
+- takala/financial_phrasebank
+- Replete-AI/code_bagel
+- athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
+- IlyaGusev/gpt_roleplay_realm
+- rickRossie/bluemoon_roleplay_chat_data_300k_messages
+- jtatman/hypnosis_dataset
+- Hypersniper/philosophy_dialogue
+- Locutusque/function-calling-chatml
+- bible-nlp/biblenlp-corpus
+- DatadudeDev/Bible
+- Helsinki-NLP/bible_para
+- HausaNLP/AfriSenti-Twitter
+- aixsatoshi/Chat-with-cosmopedia
+- HuggingFaceTB/cosmopedia-100k
+- HuggingFaceFW/fineweb-edu
+- m-a-p/CodeFeedback-Filtered-Instruction
+- heliosbrahma/mental_health_chatbot_dataset
 pipeline_tag: text-generation
 ---