92 lines
3.0 KiB
Markdown
92 lines
3.0 KiB
Markdown
---
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tags:
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- merge
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- mergekit
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- lazymergekit
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- mlabonne/ChimeraLlama-3-8B-v2
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- nbeerbower/llama-3-stella-8B
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- uygarkurt/llama-3-merged-linear
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base_model:
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- mlabonne/ChimeraLlama-3-8B-v2
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- nbeerbower/llama-3-stella-8B
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- uygarkurt/llama-3-merged-linear
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license: other
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---
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# NeuralLLaMa-3-8b-DT-v0.1
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NeuralLLaMa-3-8b-DT-v0.1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [mlabonne/ChimeraLlama-3-8B-v2](https://huggingface.co/mlabonne/ChimeraLlama-3-8B-v2)
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* [nbeerbower/llama-3-stella-8B](https://huggingface.co/nbeerbower/llama-3-stella-8B)
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* [uygarkurt/llama-3-merged-linear](https://huggingface.co/uygarkurt/llama-3-merged-linear)
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## 🧩 Configuration
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```yaml
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models:
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- model: NousResearch/Meta-Llama-3-8B
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# No parameters necessary for base model
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- model: mlabonne/ChimeraLlama-3-8B-v2
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parameters:
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density: 0.33
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weight: 0.2
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- model: nbeerbower/llama-3-stella-8B
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parameters:
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density: 0.44
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weight: 0.4
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- model: uygarkurt/llama-3-merged-linear
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parameters:
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density: 0.55
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weight: 0.4
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merge_method: dare_ties
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base_model: NousResearch/Meta-Llama-3-8B
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parameters:
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int8_mask: true
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dtype: float16
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```
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## 🗨️ Chats
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate bitsandbytes
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, BitsAndBytesConfig
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import torch
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bnb_config = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_use_double_quant=True,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_compute_dtype=torch.bfloat16
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)
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MODEL_NAME = 'Kukedlc/NeuralLLaMa-3-8b-DT-v0.1'
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map='cuda:0', quantization_config=bnb_config)
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prompt_system = "You are an advanced language model that speaks Spanish fluently, clearly, and precisely.\
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You are called Roberto the Robot and you are an aspiring post-modern artist."
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prompt = "Create a piece of art that represents how you see yourself, Roberto, as an advanced LLm, with ASCII art, mixing diagrams, engineering and let yourself go."
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chat = [
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{"role": "system", "content": f"{prompt_system}"},
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{"role": "user", "content": f"{prompt}"},
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]
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chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(chat, return_tensors="pt").to('cuda')
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streamer = TextStreamer(tokenizer)
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stop_token = "<|eot_id|>"
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stop = tokenizer.encode(stop_token)[0]
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_ = model.generate(**inputs, streamer=streamer, max_new_tokens=1024, do_sample=True, temperature=0.7, repetition_penalty=1.2, top_p=0.9, eos_token_id=stop)
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``` |