Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- mamba-hf
+---
+
+# MambaHermes-3B
+
+<img src="https://th.bing.com/th/id/OIG.Jp5dA01tOAFcwSp544nv?pid=ImgGn" width="300" height="300" alt="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=device, trust_remote_code=True, dtype=torch.float16)
+
+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(eos, "")
+)
+
+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)
+