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Model: anwgpt/anwllama-1-chat Source: Original Platform
2026-06-15 00:07:40 +08:00
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--- a/.gitattributes
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--- a/README.md
+++ b/README.md
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+---
+license: mit
+language:
+- en
+library_name: transformers
+---
+
+# anwllama 1
+
+Introducing `anwllama 1`! A experimental version of `anwgpt4` using llama architecture!
+
+Now it uses ChatLM format!
+
+The model is under trained
+
+```
+User: What is artificial intelligence?
+Assistant: Yes, one can do this in-depth data.  It does not have the capability to test and optimize their research. The algorithm can be used as an array of tasks, such as data or applications, using the process of solving and testing methods.
+
+--------------------------------------------------
+
+User: How do neural networks work?
+Assistant: Yes, some high-quality devices that use artificial intelligence can be used to solve a problem-solving process and provide a comprehensive value for their security. It is often used in technology, allowing for more efficient solutions and strategies to improve communication. Additionally, solar-based systems also helps reduce air pollution, including reducing performance, depression, and improved costs.
+
+--------------------------------------------------
+
+User: Who created you?
+Assistant: Unitedes would be used to create an algorithm with the result of data, including the following:
+
+1. Open the data from the user and enter the data
+2. The program should then display the data in the server
+3. Use the input array to ensure that the data is invalid or not in use
+4. If it is done by the input input and then the user has any questions or concerns about how it can handle the input value of the data
+5. Finally, the program will find the number of examples in the code for each data and the amount required to be calculated
+```
--- a/chat_template.jinja
+++ b/chat_template.jinja
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+{% for message in messages %}
+{% if message['role'] == 'user' %}
+{{ '<|user|>
+' + message['content'] + eos_token }}
+{% elif message['role'] == 'system' %}
+{{ '<|system|>
+' + message['content'] + eos_token }}
+{% elif message['role'] == 'assistant' %}
+{{ '<|assistant|>
+'  + message['content'] + eos_token }}
+{% endif %}
+{% if loop.last and add_generation_prompt %}
+{{ '<|assistant|>' }}
+{% endif %}
+{% endfor %}
--- a/checkpoint-1400/chat_template.jinja
+++ b/checkpoint-1400/chat_template.jinja
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+{% for message in messages %}
+{% if message['role'] == 'user' %}
+{{ '<|user|>
+' + message['content'] + eos_token }}
+{% elif message['role'] == 'system' %}
+{{ '<|system|>
+' + message['content'] + eos_token }}
+{% elif message['role'] == 'assistant' %}
+{{ '<|assistant|>
+'  + message['content'] + eos_token }}
+{% endif %}
+{% if loop.last and add_generation_prompt %}
+{{ '<|assistant|>' }}
+{% endif %}
+{% endfor %}
--- a/checkpoint-1400/config.json
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+{
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--- a/checkpoint-1500/chat_template.jinja
+++ b/checkpoint-1500/chat_template.jinja
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+{% for message in messages %}
+{% if message['role'] == 'user' %}
+{{ '<|user|>
+' + message['content'] + eos_token }}
+{% elif message['role'] == 'system' %}
+{{ '<|system|>
+' + message['content'] + eos_token }}
+{% elif message['role'] == 'assistant' %}
+{{ '<|assistant|>
+'  + message['content'] + eos_token }}
+{% endif %}
+{% if loop.last and add_generation_prompt %}
+{{ '<|assistant|>' }}
+{% endif %}
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--- a/checkpoint-1500/config.json
+++ b/checkpoint-1500/config.json
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+++ b/checkpoint-1500/training_args.bin
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+version https://git-lfs.github.com/spec/v1
+oid sha256:0dbcdc47543731af5d7dd1c833f58eff8fc4bfa98ba06b89b2b240e832937ee6
+size 5137
--- a/config.json
+++ b/config.json
@@ -0,0 +1,32 @@
+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1024,
+  "max_position_embeddings": 2048,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 6,
+  "num_hidden_layers": 6,
+  "num_key_value_heads": 2,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 10000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.0.0",
+  "use_cache": false,
+  "vocab_size": 32002
+}
--- a/generation_config.json
+++ b/generation_config.json
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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "transformers_version": "5.0.0",
+  "use_cache": false
+}
--- a/model.safetensors
+++ b/model.safetensors
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+version https://git-lfs.github.com/spec/v1
+oid sha256:2246291c11ae8944198f2a9027cc15a284ef966c7ea423ba4ec831bf68bea4db
+size 136085144
--- a/model_metadata.json
+++ b/model_metadata.json
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+{
+  "model_name": "i3-Llama-ChatML",
+  "architecture": "LlamaForCausalLM",
+  "format": "ChatML",
+  "parameters": 34019712,
+  "vocab_size": 32002
+}
--- a/tokenizer.json
+++ b/tokenizer.json
--- a/tokenizer_config.json
+++ b/tokenizer_config.json
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+{
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "is_local": false,
+  "legacy": false,
+  "model_max_length": 2048,
+  "pad_token": "</s>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}