--- license: wtfpl language: - en tags: - mamba-hf --- # MambaHermes-3B mamba-hf Mamba Models with hf_integration. For modeling codes: [**mamba-hf**](https://github.com/LegallyCoder/mamba-hf) # Usage: ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM CHAT_TEMPLATE_ID = "HuggingFaceH4/zephyr-7b-beta" device = "cuda:0" if torch.cuda.is_available() else "cpu" model_name = "Q-bert/MambaHermes-3B" eos_token = "<|endoftext|>" tokenizer = AutoTokenizer.from_pretrained(model_name) tokenizer.eos_token = eos_token tokenizer.pad_token = tokenizer.eos_token tokenizer.chat_template = AutoTokenizer.from_pretrained(CHAT_TEMPLATE_ID).chat_template model = AutoModelForCausalLM.from_pretrained( model_name, device_map=device, trust_remote_code=True) messages = [] prompt = "Tell me 5 sites to visit in Spain" messages.append(dict(role="user", content=prompt)) input_ids = tokenizer.apply_chat_template( messages, return_tensors="pt", add_generation_prompt=True ).to(device) out = model.generate( input_ids=input_ids, max_length=2000, temperature=0.9, top_p=0.7, eos_token_id=tokenizer.eos_token_id, ) decoded = tokenizer.batch_decode(out) assistant_message = ( decoded[0].split("<|assistant|>\n")[-1].replace(tokenizer.eos_token, "") ) print(assistant_message) ``` # For Training: ```python from transformers import Trainer ,TrainingArguments import torch import os class MambaTrainer(Trainer): def compute_loss(self, model, inputs, return_outputs=False): input_ids = inputs.pop("input_ids") lm_logits = model(input_ids)[0] labels = input_ids.to(lm_logits.device) shift_logits = lm_logits[:, :-1, :].contiguous() labels = labels[:, 1:].contiguous() loss_fct = torch.nn.CrossEntropyLoss() lm_loss = loss_fct(shift_logits.view(-1, shift_logits.size(-1)), labels.view(-1)) return lm_loss ``` You must use this class for training. And fp16 must be **False**. # Credits: https://huggingface.co/state-spaces https://huggingface.co/clibrain/mamba-2.8b-instruct-openhermes Special thanks to Albert Gu and Tri Dao for their articles. (https://arxiv.org/abs/2312.00752)