Text Generation
Transformers
Safetensors
llama
mergekit
Merge
Not-For-All-Audiences
conversational
text-generation-inference
Instructions to use TareksGraveyard/Maleficent-R1-LLaMa-70B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TareksGraveyard/Maleficent-R1-LLaMa-70B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TareksGraveyard/Maleficent-R1-LLaMa-70B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TareksGraveyard/Maleficent-R1-LLaMa-70B") model = AutoModelForCausalLM.from_pretrained("TareksGraveyard/Maleficent-R1-LLaMa-70B", device_map="auto") 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 TareksGraveyard/Maleficent-R1-LLaMa-70B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TareksGraveyard/Maleficent-R1-LLaMa-70B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TareksGraveyard/Maleficent-R1-LLaMa-70B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/TareksGraveyard/Maleficent-R1-LLaMa-70B
- SGLang
How to use TareksGraveyard/Maleficent-R1-LLaMa-70B 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 "TareksGraveyard/Maleficent-R1-LLaMa-70B" \ --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": "TareksGraveyard/Maleficent-R1-LLaMa-70B", "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 "TareksGraveyard/Maleficent-R1-LLaMa-70B" \ --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": "TareksGraveyard/Maleficent-R1-LLaMa-70B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use TareksGraveyard/Maleficent-R1-LLaMa-70B with Docker Model Runner:
docker model run hf.co/TareksGraveyard/Maleficent-R1-LLaMa-70B
metadata
base_model:
- huihui-ai/Llama-3.3-70B-Instruct-abliterated
- TheDrummer/Fallen-Llama-3.3-R1-70B-v1
- Sao10K/L3-70B-Euryale-v2.1
- SicariusSicariiStuff/Negative_LLAMA_70B
library_name: transformers
tags:
- mergekit
- merge
- not-for-all-audiences
license: llama3.3
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SCE merge method using huihui-ai/Llama-3.3-70B-Instruct-abliterated as a base.
Models Merged
The following models were included in the merge:
- TheDrummer/Fallen-Llama-3.3-R1-70B-v1
- Sao10K/L3-70B-Euryale-v2.1
- SicariusSicariiStuff/Negative_LLAMA_70B
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Sao10K/L3-70B-Euryale-v2.1
- model: SicariusSicariiStuff/Negative_LLAMA_70B
- model: TheDrummer/Fallen-Llama-3.3-R1-70B-v1
merge_method: sce
chat_template: llama3
base_model: huihui-ai/Llama-3.3-70B-Instruct-abliterated
parameters:
select_topk: 0.80
dtype: float32
out_dtype: bfloat16
tokenizer:
source: union