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Model: tiny-random/llama-3 Source: Original Platform
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98
README.md
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README.md
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---
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library_name: transformers
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base_model:
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- meta-llama/Llama-3.3-70B-Instruct
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---
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This tiny model is intended for debugging. It is randomly initialized using the configuration adapted from [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct).
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### Example usage:
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```python
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from transformers import pipeline
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model_id = "tiny-random/llama-3"
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pipe = pipeline(
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"text-generation", model=model_id, device="cuda",
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trust_remote_code=True, max_new_tokens=3,
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)
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print(pipe("Hello World!"))
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```
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### Codes to create this repo:
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```python
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import torch
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from transformers import (
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AutoConfig,
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AutoModelForCausalLM,
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AutoTokenizer,
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GenerationConfig,
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pipeline,
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set_seed,
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)
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source_model_id = "meta-llama/Llama-3.3-70B-Instruct"
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save_folder = "/tmp/tiny-random/llama-3"
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tokenizer = AutoTokenizer.from_pretrained(
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source_model_id, trust_remote_code=True,
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)
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tokenizer.save_pretrained(save_folder)
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config = AutoConfig.from_pretrained(
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source_model_id, trust_remote_code=True,
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)
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config.hidden_size = 8
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config.intermediate_size = 64
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config.num_attention_heads = 16
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config.num_key_value_heads = 8
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config.head_dim = 32
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config.num_hidden_layers = 2
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model = AutoModelForCausalLM.from_config(
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config,
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torch_dtype=torch.bfloat16,
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trust_remote_code=True,
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)
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model.generation_config = GenerationConfig.from_pretrained(
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source_model_id, trust_remote_code=True,
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)
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set_seed(42)
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model = model.cpu()
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with torch.no_grad():
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for name, p in sorted(model.named_parameters()):
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torch.nn.init.normal_(p, 0, 0.1)
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print(name, p.shape)
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model.save_pretrained(save_folder)
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```
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### Printing the model:
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```text
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LlamaForCausalLM(
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(model): LlamaModel(
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(embed_tokens): Embedding(128256, 8)
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(layers): ModuleList(
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(0-1): 2 x LlamaDecoderLayer(
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(self_attn): LlamaAttention(
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(q_proj): Linear(in_features=8, out_features=512, bias=False)
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(k_proj): Linear(in_features=8, out_features=256, bias=False)
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(v_proj): Linear(in_features=8, out_features=256, bias=False)
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(o_proj): Linear(in_features=512, out_features=8, bias=False)
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)
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(mlp): LlamaMLP(
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(gate_proj): Linear(in_features=8, out_features=64, bias=False)
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(up_proj): Linear(in_features=8, out_features=64, bias=False)
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(down_proj): Linear(in_features=64, out_features=8, bias=False)
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(act_fn): SiLUActivation()
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)
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(input_layernorm): LlamaRMSNorm((8,), eps=1e-05)
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(post_attention_layernorm): LlamaRMSNorm((8,), eps=1e-05)
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)
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)
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(norm): LlamaRMSNorm((8,), eps=1e-05)
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(rotary_emb): LlamaRotaryEmbedding()
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)
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(lm_head): Linear(in_features=8, out_features=128256, bias=False)
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)
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```
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109
chat_template.jinja
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chat_template.jinja
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{{- bos_token }}
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{%- if custom_tools is defined %}
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{%- set tools = custom_tools %}
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{%- endif %}
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{%- if not tools_in_user_message is defined %}
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{%- set tools_in_user_message = true %}
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{%- endif %}
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{%- if not date_string is defined %}
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{%- set date_string = "26 Jul 2024" %}
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{%- endif %}
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{%- if not tools is defined %}
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{%- set tools = none %}
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{%- endif %}
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{#- This block extracts the system message, so we can slot it into the right place. #}
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{%- set system_message = "" %}
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{%- endif %}
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{#- System message + builtin tools #}
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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{%- if builtin_tools is defined or tools is not none %}
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{{- "Environment: ipython\n" }}
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{%- endif %}
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{%- if builtin_tools is defined %}
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{{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
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{%- endif %}
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{{- "Cutting Knowledge Date: December 2023\n" }}
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{{- "Today Date: " + date_string + "\n\n" }}
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{%- if tools is not none and not tools_in_user_message %}
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{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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{{- "Do not use variables.\n\n" }}
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{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{%- endif %}
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{{- system_message }}
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{{- "<|eot_id|>" }}
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{#- Custom tools are passed in a user message with some extra guidance #}
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{%- if tools_in_user_message and not tools is none %}
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{#- Extract the first user message so we can plug it in here #}
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{%- if messages | length != 0 %}
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{%- set first_user_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
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{%- endif %}
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{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
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{{- "Given the following functions, please respond with a JSON for a function call " }}
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{{- "with its proper arguments that best answers the given prompt.\n\n" }}
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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{{- "Do not use variables.\n\n" }}
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{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{{- first_user_message + "<|eot_id|>"}}
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{%- endif %}
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{%- for message in messages %}
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{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
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{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
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{%- elif 'tool_calls' in message %}
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{%- if not message.tool_calls|length == 1 %}
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{{- raise_exception("This model only supports single tool-calls at once!") }}
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{%- endif %}
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{%- set tool_call = message.tool_calls[0].function %}
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{%- if builtin_tools is defined and tool_call.name in builtin_tools %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
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{{- "<|python_tag|>" + tool_call.name + ".call(" }}
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{%- for arg_name, arg_val in tool_call.arguments | items %}
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{{- arg_name + '="' + arg_val + '"' }}
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{%- if not loop.last %}
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{{- ", " }}
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{%- endif %}
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{%- endfor %}
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{{- ")" }}
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{%- else %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
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{{- '{"name": "' + tool_call.name + '", ' }}
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{{- '"parameters": ' }}
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{{- tool_call.arguments | tojson }}
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{{- "}" }}
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{%- endif %}
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{%- if builtin_tools is defined %}
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{#- This means we're in ipython mode #}
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{{- "<|eom_id|>" }}
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{%- else %}
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{{- "<|eot_id|>" }}
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{%- endif %}
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{%- elif message.role == "tool" or message.role == "ipython" %}
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{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
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{%- if message.content is mapping or message.content is iterable %}
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{{- message.content | tojson }}
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{%- else %}
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{{- message.content }}
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{%- endif %}
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{{- "<|eot_id|>" }}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
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{%- endif %}
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39
config.json
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"dtype": "bfloat16",
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"eos_token_id": [
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128001,
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128008,
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128009
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],
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"head_dim": 32,
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"hidden_act": "silu",
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"hidden_size": 8,
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"initializer_range": 0.02,
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"intermediate_size": 64,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 16,
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"num_hidden_layers": 2,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.1",
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"use_cache": true,
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"vocab_size": 128256
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}
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generation_config.json
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generation_config.json
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{
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"bos_token_id": 128000,
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"do_sample": true,
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"eos_token_id": [
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128001,
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128008,
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128009
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],
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.57.1",
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"trust_remote_code": true
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}
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3
model.safetensors
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3
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e74fe117d2c36a3970a4cf5bda861dbba97d8daef4eb247a65e407b8ba81f3ff
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size 4161768
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special_tokens_map.json
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|begin_of_text|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|eot_id|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<|finetune_right_pad_id|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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3
tokenizer.json
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
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size 17209920
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2063
tokenizer_config.json
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2063
tokenizer_config.json
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