Text Generation
Transformers
Safetensors
mistral
mergekit
Merge
model_stock
conversational
text-generation-inference
Instructions to use EldritchLabs/Altair-Stock-12B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EldritchLabs/Altair-Stock-12B-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="EldritchLabs/Altair-Stock-12B-v1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("EldritchLabs/Altair-Stock-12B-v1") model = AutoModelForCausalLM.from_pretrained("EldritchLabs/Altair-Stock-12B-v1", 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 EldritchLabs/Altair-Stock-12B-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EldritchLabs/Altair-Stock-12B-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EldritchLabs/Altair-Stock-12B-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/EldritchLabs/Altair-Stock-12B-v1
- SGLang
How to use EldritchLabs/Altair-Stock-12B-v1 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 "EldritchLabs/Altair-Stock-12B-v1" \ --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": "EldritchLabs/Altair-Stock-12B-v1", "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 "EldritchLabs/Altair-Stock-12B-v1" \ --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": "EldritchLabs/Altair-Stock-12B-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use EldritchLabs/Altair-Stock-12B-v1 with Docker Model Runner:
docker model run hf.co/EldritchLabs/Altair-Stock-12B-v1
Upload mergekit_config.yml with huggingface_hub
Browse files- mergekit_config.yml +20 -0
mergekit_config.yml
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architecture: MistralForCausalLM
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base_model: B:\12B\!models--mistralai--Mistral-Nemo-Instruct-2407
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merge_method: model_stock
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models:
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- model: B:\12B\!models--mistralai--Mistral-Nemo-Instruct-2407
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- model: B:\12B\!models--anthracite-org--magnum-v4-12b
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- model: B:\12B\!models--ArliAI--Mistral-Nemo-12B-ArliAI-RPMax-v1.2
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- model: B:\12B\!models--Fizzarolli--MN-12b-Rosier-v1
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- model: B:\12B\!models--HumanLLMs--Human-Like-Mistral-Nemo-Instruct-2407
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- model: B:\12B\!models--inflatebot--MN-12B-Mag-Mell-R1
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- model: B:\12B\!models--KOOWEEYUS--BlackSheep-RP-12B
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- model: B:\12B\!models--Lambent--Arsenic-Shahrazad-12B-v3
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- model: B:\12B\!models--SicariusSicariiStuff--Impish_Bloodmoon_12B
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- model: B:\12B\!models--SuperbEmphasis--MN-12b-RP-Ink-RP-Longform
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parameters:
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filter_wise: false
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dtype: bfloat16
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tokenizer:
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source: base
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name: 🦅 Altair-Stock-12B-v1
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