upload model

README.md

@@ -1,3 +1,94 @@
 ---
 license: gpl-3.0
+language:
+- en
 ---
+# NanoLM-25M-Instruct-v1.1
+
+
+English | [简体中文](README_zh-CN.md)
+
+
+## Introduction
+
+In order to explore the potential of small models, I have attempted to build a series of them, which are available in the [NanoLM Collections](https://huggingface.co/collections/Mxode/nanolm-66d6d75b4a69536bca2705b2).
+
+This is NanoLM-25M-Instruct-v1.1. The model currently supports **English only**.
+
+
+
+## Model Details
+
+| Nano LMs | Non-emb Params | Arch | Layers | Dim | Heads | Seq Len |
+| :----------: | :------------------: | :---: | :----: | :-------: | :---: | :---: |
+| **25M**         | **15M**  |   **MistralForCausalLM**     | **12**      | **312**     | **12**    | **2K** |
+| 70M         | 42M |  LlamaForCausalLM          | 12     | 576    | 9   |2K|
+| 0.3B         | 180M |  Qwen2ForCausalLM  | 12   | 896    | 14 |4K|
+| 1B     | 840M | Qwen2ForCausalLM | 18   | 1536   | 12   |4K|
+
+
+
+## How to use
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = 'Mxode/NanoLM-25M-Instruct-v1.1'
+
+model = AutoModelForCausalLM.from_pretrained(model_path).to('cuda:0', torch.bfloat16)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+
+def get_response(prompt: str, **kwargs):
+    generation_args = dict(
+        max_new_tokens = kwargs.pop("max_new_tokens", 512),
+        do_sample = kwargs.pop("do_sample", True),
+        temperature = kwargs.pop("temperature", 0.7),
+        top_p = kwargs.pop("top_p", 0.8),
+        top_k = kwargs.pop("top_k", 40),
+        **kwargs
+    )
+
+    messages = [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": prompt}
+    ]
+    text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+    model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+    generated_ids = model.generate(model_inputs.input_ids, **generation_args)
+    generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+    ]
+
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return response
+
+
+prompt1 = "What can you do for me?"
+print(get_response(prompt1, do_sample=False))
+
+"""
+I'm so glad you asked! I'm a large language model, so I don't have personal experiences or emotions, but I can provide information and assist with tasks to help with your tasks.
+
+Here are some ways I can assist you:
+
+1. **Answer questions**: I can provide information on a wide range of topics, from science and history to entertainment and culture.
+2. **Generate text**: I can create text based on a prompt or topic, and can even help with writing tasks such as proofreading and editing.
+3. **Translate text**: I can translate text from one language to another, including popular languages such as Spanish, French, German, Chinese, and many more.
+4. **Summarize content**: I can summarize long pieces of text, such as articles or documents, into shorter, more digestible versions.
+5. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, books, or movies.
+6. **Chat and converse**: I can engage in natural-sounding conversations, using context and understanding to respond to questions and statements.
+7. **Play games**: I can play simple text-based games, such as 20 Questions, Hangman, or Word Jumble.
+8. **Provide definitions**: I can define words and phrases, explaining their meanings and usage.
+9. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, or books to read.
+10. **Entertain**: I can engage in fun conversations, tell jokes, and even create simple games or puzzles.
+
+Which of these methods would you like to do?
+"""
+```

README_zh-CN.md

@@ -0,0 +1,86 @@
+# NanoLM-25M-Instruct-v1.1
+
+[English](README.md) | 简体中文
+
+
+## Introduction
+
+为了探究小模型的潜能，我尝试构建一系列小模型，并存放于 [NanoLM Collections](https://huggingface.co/collections/Mxode/nanolm-66d6d75b4a69536bca2705b2)。
+
+这是 NanoLM-25M-Instruct-v1.1。该模型目前仅支持**英文**。
+
+
+## 模型详情
+
+| Nano LMs | Non-emb Params | Arch | Layers | Dim | Heads | Seq Len |
+| :----------: | :------------------: | :---: | :----: | :-------: | :---: | :---: |
+| **25M**         | **15M**  |   **MistralForCausalLM**     | **12**      | **312**     | **12**    | **2K** |
+| 70M         | 42M |  LlamaForCausalLM          | 12     | 576    | 9   |2K|
+| 0.3B         | 180M |  Qwen2ForCausalLM  | 12   | 896    | 14 |4K|
+| 1B     | 840M | Qwen2ForCausalLM | 18   | 1536   | 12   |4K|
+
+
+## 如何使用
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = 'Mxode/NanoLM-25M-Instruct-v1.1'
+
+model = AutoModelForCausalLM.from_pretrained(model_path).to('cuda:0', torch.bfloat16)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+
+def get_response(prompt: str, **kwargs):
+    generation_args = dict(
+        max_new_tokens = kwargs.pop("max_new_tokens", 512),
+        do_sample = kwargs.pop("do_sample", True),
+        temperature = kwargs.pop("temperature", 0.7),
+        top_p = kwargs.pop("top_p", 0.8),
+        top_k = kwargs.pop("top_k", 40),
+        **kwargs
+    )
+
+    messages = [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": prompt}
+    ]
+    text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+    model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+    generated_ids = model.generate(model_inputs.input_ids, **generation_args)
+    generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+    ]
+
+    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return response
+
+
+prompt1 = "What can you do for me?"
+print(get_response(prompt1, do_sample=False))
+
+"""
+I'm so glad you asked! I'm a large language model, so I don't have personal experiences or emotions, but I can provide information and assist with tasks to help with your tasks.
+
+Here are some ways I can assist you:
+
+1. **Answer questions**: I can provide information on a wide range of topics, from science and history to entertainment and culture.
+2. **Generate text**: I can create text based on a prompt or topic, and can even help with writing tasks such as proofreading and editing.
+3. **Translate text**: I can translate text from one language to another, including popular languages such as Spanish, French, German, Chinese, and many more.
+4. **Summarize content**: I can summarize long pieces of text, such as articles or documents, into shorter, more digestible versions.
+5. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, books, or movies.
+6. **Chat and converse**: I can engage in natural-sounding conversations, using context and understanding to respond to questions and statements.
+7. **Play games**: I can play simple text-based games, such as 20 Questions, Hangman, or Word Jumble.
+8. **Provide definitions**: I can define words and phrases, explaining their meanings and usage.
+9. **Offer suggestions**: I can provide suggestions for things like gift ideas, travel destinations, or books to read.
+10. **Entertain**: I can engage in fun conversations, tell jokes, and even create simple games or puzzles.
+
+Which of these methods would you like to do?
+"""
+```

added_tokens.json

@@ -0,0 +1,6 @@
+{
+  "<image>": 32003,
+  "<|endoftext|>": 32002,
+  "<|im_end|>": 32001,
+  "<|im_start|>": 32000
+}

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "Mxode/NanoLM-25M-Instruct-v1.1",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 32001,
+  "hidden_act": "silu",
+  "hidden_size": 312,
+  "initializer_range": 0.02,
+  "intermediate_size": 1092,
+  "max_position_embeddings": 2048,
+  "model_type": "mistral",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "num_key_value_heads": 4,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 10000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.42.0",
+  "use_cache": false,
+  "vocab_size": 32064
+}

generation_config.json

@@ -0,0 +1,10 @@
+{
+  "do_sample": true,
+  "eos_token_id": 32001,
+  "max_new_tokens": 2048,
+  "pad_token_id": 32002,
+  "temperature": 0.3,
+  "top_k": 20,
+  "top_p": 0.7,
+  "transformers_version": "4.42.0"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8bb6070b60572394fb56490f37489c8774f4ab3591d691be2809003733137724
+size 50796360

special_tokens_map.json

@@ -0,0 +1,36 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|endoftext|>",
+    "<image>"
+  ],
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

tokenizer_config.json

@@ -0,0 +1,83 @@
+{
+  "add_bos_token": false,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32002": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32003": {
+      "content": "<image>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|endoftext|>",
+    "<image>"
+  ],
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "legacy": true,
+  "model_max_length": 2048,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}