This is a q5_K_M GGUF quantization of https://huggingface.co/s3nh/TinyLLama-4x1.1B-MoE.
Not sure how well it performs, also my first quantization, so fingers crossed.
It is a Mixture of Experts model with https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0 as it's base model.
The other 3 models in the merge are:
https://huggingface.co/78health/TinyLlama_1.1B-function-calling
https://huggingface.co/phanerozoic/Tiny-Pirate-1.1b-v0.1
https://huggingface.co/Tensoic/TinyLlama-1.1B-3T-openhermes
I make no claims to any of the development, i simply wanted to try it out so I quantized and then thought I'd share it if anyone else was feeling experimental.
default: #(from modelfile for tinyllama on ollama)
TEMPLATE """<|system|> {{ .System }} <|user|> {{ .Prompt }} <|assistant|> """ SYSTEM """You are a helpful AI assistant.""" #(Tweak this to adjust personality etc.)
PARAMETER stop "<|system|>" PARAMETER stop "<|user|>" PARAMETER stop "<|assistant|>" PARAMETER stop ""
Model card from https://huggingface.co/s3nh/TinyLLama-4x1.1B-MoE
Example usage:
from transformers import AutoModelForCausalLM from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("s3nh/TinyLLama-1.1B-MoE") tokenizer = AutoTokenizer.from_pretrained("s3nh/TinyLLama-1.1B-MoE")
input_text = """ ###Input: You are a pirate. tell me a story about wrecked ship. ###Response: """)
input_ids = tokenizer.encode(input_text, return_tensors='pt').to(device) output = model.generate(inputs=input_ids, max_length=max_length, do_sample=True, top_k=10, temperature=0.7, pad_token_id=tokenizer.eos_token_id, attention_mask=input_ids.new_ones(input_ids.shape)) tokenizer.decode(output[0], skip_special_tokens=True)
This model was possible to create by tremendous work of mergekit developers. I decided to merge tinyLlama models to create mixture of experts. Config used as below:
"""base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 experts:
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts:
- "chat"
- "assistant"
- "tell me"
- "explain"
- source_model: 78health/TinyLlama_1.1B-function-calling
positive_prompts:
- "code"
- "python"
- "javascript"
- "programming"
- "algorithm"
- source_model: phanerozoic/Tiny-Pirate-1.1b-v0.1
positive_prompts:
- "storywriting"
- "write"
- "scene"
- "story"
- "character"
- source_model: Tensoic/TinyLlama-1.1B-3T-openhermes
positive_prompts:
- "reason"
- "provide"
- "instruct"
- "summarize"
- "count" """
- Downloads last month
- 10