Instructions to use cgus/NemoMix-Unleashed-12B-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cgus/NemoMix-Unleashed-12B-exl2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="cgus/NemoMix-Unleashed-12B-exl2") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("cgus/NemoMix-Unleashed-12B-exl2") model = AutoModelForCausalLM.from_pretrained("cgus/NemoMix-Unleashed-12B-exl2", 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 cgus/NemoMix-Unleashed-12B-exl2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cgus/NemoMix-Unleashed-12B-exl2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cgus/NemoMix-Unleashed-12B-exl2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cgus/NemoMix-Unleashed-12B-exl2
- SGLang
How to use cgus/NemoMix-Unleashed-12B-exl2 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 "cgus/NemoMix-Unleashed-12B-exl2" \ --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": "cgus/NemoMix-Unleashed-12B-exl2", "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 "cgus/NemoMix-Unleashed-12B-exl2" \ --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": "cgus/NemoMix-Unleashed-12B-exl2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use cgus/NemoMix-Unleashed-12B-exl2 with Docker Model Runner:
docker model run hf.co/cgus/NemoMix-Unleashed-12B-exl2
Upload 6 files
Browse files- README.md +102 -0
- config.json +38 -0
- output.safetensors +3 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer_config.json +0 -0
README.md
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---
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base_model: []
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# Information
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## Details
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Okay, I tried really hard to improve my ChatML merges, but that has gone terribly wrong. Everyone is adding special tokens with different IDs so can't even make a proper union tokenizer for them, damn. Not to mention, I made some... interesting discoveres in regards to some models' context lenghts. You can watch the breakdown of how it went down here: https://www.captiongenerator.com/v/2303039/marinaraspaghetti's-merging-experience.
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This one feels a bit different to my previous attempts and seems less prone to repetition, especially on higher contexts, which is great for me! I'll probably improve on it even further, but for now, it feels rather nice. Great for RP and storytelling. All credits and thanks go to the amazing MistralAI, Intervitens, Sao10K and Nbeerbower for their amazing models! Plus, special shoutouts to Parasitic Rogue for ideas and Prodeus Unity and Statuo for cool exl2 quants of my previous merges. Cheers to folks over at the Drummer's server! Have a good one, everyone.
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## Instruct
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*Sigh,* Mistral Instruct, I'm afraid.
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```
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<s>[INST] {system} [/INST]{response}</s>[INST] {user's message} [/INST]{response}</s>
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```
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## Parameters
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I recommend running Temperature 1.0-1.25 with 0.1 Top A or 0.01-0.1 Min P, and with 0.8/1.75/2/0 DRY. Also works with lower Temperatures below 1.0. Nothing more needed.
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### Settings
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You can use my exact settings from here (use the ones from the Mistral Base/Customized folder, I also recommend checking the Mistral Improved folder): https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main.
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## GGUF
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https://huggingface.co/bartowski/NemoMix-Unleashed-12B-GGUF
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## EXL2
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https://huggingface.co/Statuo/NemoMix-Unleashed-EXL2-8bpw
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# NemoMix-Unleashed-12B
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the della_linear merge method using E:\mergekit\mistralaiMistral-Nemo-Base-2407 as a base.
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### Models Merged
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The following models were included in the merge:
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* E:\mergekit\intervitens_mini-magnum-12b-v1.1
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* E:\mergekit\nbeerbower_mistral-nemo-bophades-12B
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* E:\mergekit\Sao10K_MN-12B-Lyra-v1
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* E:\mergekit\nbeerbower_mistral-nemo-gutenberg-12B
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* E:\mergekit\mistralaiMistral-Nemo-Instruct-2407
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: E:\mergekit\mistralaiMistral-Nemo-Instruct-2407
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parameters:
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weight: 0.1
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density: 0.4
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- model: E:\mergekit\nbeerbower_mistral-nemo-bophades-12B
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parameters:
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weight: 0.12
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density: 0.5
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- model: E:\mergekit\nbeerbower_mistral-nemo-gutenberg-12B
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parameters:
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weight: 0.2
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density: 0.6
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- model: E:\mergekit\Sao10K_MN-12B-Lyra-v1
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parameters:
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weight: 0.25
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density: 0.7
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- model: E:\mergekit\intervitens_mini-magnum-12b-v1.1
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parameters:
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weight: 0.33
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density: 0.8
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merge_method: della_linear
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base_model: E:\mergekit\mistralaiMistral-Nemo-Base-2407
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parameters:
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epsilon: 0.05
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lambda: 1
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dtype: bfloat16
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tokenizer_source: base
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```
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# Ko-fi
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## Enjoying what I do? Consider donating here, thank you!
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https://ko-fi.com/spicy_marinara
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config.json
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{
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"_name_or_path": "E:\\mergekit\\mistralaiMistral-Nemo-Base-2407",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 1024000,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 40,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.0",
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"use_cache": true,
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"vocab_size": 131072,
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"quantization_config": {
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"quant_method": "exl2",
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"version": "0.1.8",
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"bits": 4.0,
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"head_bits": 6,
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"calibration": {
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"rows": 115,
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"length": 2048,
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"dataset": "(default)"
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}
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}
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}
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output.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:dd01244fe1070690dd301a4243cee4f2180223fdeb810433a40877aa7a81762b
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size 7326533868
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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