初始化项目，由ModelHub XC社区提供模型
Model: mesolitica/mallam-5b-20k-instructions Source: Original Platform
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README.md
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---
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language:
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- ms
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---
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# Full Parameter Finetuning MaLLaM 🌙 5B 20480 context length on Malaysian instructions dataset
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README at https://github.com/mesolitica/malaya/tree/5.1/session/mistral#mallam-5b
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We use exact Mistral Instruct chat template.
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WandB, https://wandb.ai/mesolitica/fpf-mallam-5b-instructions-16k?workspace=user-husein-mesolitica
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WandB report, https://wandb.ai/mesolitica/fpf-mallam-5b-instructions-16k/reports/Instruction-finetuning--Vmlldzo2MjE5Njg2
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## Dataset
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Dataset gathered at https://huggingface.co/collections/mesolitica/malaysian-synthetic-dataset-656c2673fe7fe0b1e9e25fe2
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Notebook to prepare dataset at https://github.com/mesolitica/malaysian-dataset/blob/master/llm-instruction/combine-malay-no-alignment-multitasks-partial-ultrachat-v2.ipynb
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## Limitations
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This model is a quick demonstration that the base model can be easily fine-tuned to achieve some performance.
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It does have minimal moderation mechanisms.
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## how-to
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
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import torch
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import json
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def parse_mistral_chat(messages, function_call = None):
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user_query = messages[-1]['content']
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users, assistants = [], []
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for q in messages[:-1]:
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if q['role'] == 'user':
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users.append(q['content'])
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elif q['role'] == 'assistant':
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assistants.append(q['content'])
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texts = ['<s>']
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if function_call:
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fs = []
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for f in function_call:
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f = json.dumps(f, indent=4)
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fs.append(f)
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fs = '\n\n'.join(fs)
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texts.append(f'\n[FUNCTIONCALL]\n{fs}\n')
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for u, a in zip(users, assistants):
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texts.append(f'[INST] {u.strip()} [/INST] {a.strip()}</s>')
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texts.append(f'[INST] {user_query.strip()} [/INST]')
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prompt = ''.join(texts).strip()
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return prompt
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TORCH_DTYPE = 'bfloat16'
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nf4_config = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_quant_type='nf4',
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bnb_4bit_use_double_quant=True,
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bnb_4bit_compute_dtype=getattr(torch, TORCH_DTYPE)
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)
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tokenizer = AutoTokenizer.from_pretrained('mesolitica/mallam-5b-20k-instructions')
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model = AutoModelForCausalLM.from_pretrained(
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'mesolitica/mallam-5b-20k-instructions',
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use_flash_attention_2 = True,
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quantization_config = nf4_config
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)
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messages = [
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{'role': 'user', 'content': 'kwsp tu apa'}
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]
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prompt = parse_mistral_chat(messages)
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inputs = tokenizer([prompt], return_tensors='pt', add_special_tokens=False).to('cuda')
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generate_kwargs = dict(
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inputs,
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max_new_tokens=1024,
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top_p=0.95,
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top_k=50,
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temperature=0.9,
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do_sample=True,
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num_beams=1,
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)
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r = model.generate(**generate_kwargs)
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tokenizer.decode(r[0])
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```
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```text
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<s> [INST] kwsp tu apa [/INST]KWSP bermaksud Kumpulan Wang Simpanan Pekerja. Ia adalah sebuah institusi simpanan persaraan yang ditubuhkan oleh Kementerian Kewangan Malaysia untuk tujuan mengumpul simpanan ahli untuk dibayar pada umur persaraan, penuh atau penuh persaraan penuh. KWSP ditubuhkan pada tahun 1951 dan mula beroperasi pada tahun 1952. KWSP adalah salah satu institusi simpanan persaraan terbesar di dunia, dengan pangkalan ahli sekitar 14 juta ahli.</s>
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```
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config.json
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{
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"_name_or_path": "fpf-5b-instructions-16k/checkpoint-9800",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 8640,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.35.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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|
||||
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00003.safetensors"
|
||||
}
|
||||
}
|
||||
36
special_tokens_map.json
Normal file
36
special_tokens_map.json
Normal file
@@ -0,0 +1,36 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<pad>",
|
||||
"<s>",
|
||||
"</s>",
|
||||
"<unk>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<pad>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a111cfad8579b68df46d4197d5409a6ccaa97c59660de340106512c390b1f6b0
|
||||
size 1344099
|
||||
57
tokenizer_config.json
Normal file
57
tokenizer_config.json
Normal file
@@ -0,0 +1,57 @@
|
||||
{
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<pad>",
|
||||
"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
|
||||
},
|
||||
"3": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<pad>",
|
||||
"<s>",
|
||||
"</s>",
|
||||
"<unk>"
|
||||
],
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": true,
|
||||
"eos_token": "</s>",
|
||||
"max_length": 20480,
|
||||
"model_input_names": [
|
||||
"input_ids",
|
||||
"attention_mask"
|
||||
],
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "<pad>",
|
||||
"stride": 0,
|
||||
"tokenizer_class": "PreTrainedTokenizerFast",
|
||||
"truncation_side": "right",
|
||||
"truncation_strategy": "longest_first",
|
||||
"unk_token": "<unk>"
|
||||
}
|
||||
Reference in New Issue
Block a user