mervinpraison/tamilan-2

Gemma 2 instruction fine tuned on Tamil Alpaca Dataset

2b 9b 27b

33 4 months ago

10 Tags
... /
model
50c578899b93 · 1.9GB
    Metadata
  • gemma2.attention.head_count
    8
  • gemma2.attention.head_count_kv
    4
  • gemma2.attention.key_length
    256
  • gemma2.attention.layer_norm_rms_epsilon
    1e-06
  • gemma2.attention.sliding_window
    4096
  • gemma2.attention.value_length
    256
  • gemma2.attn_logit_softcapping
    50
  • gemma2.block_count
    26
  • gemma2.context_length
    8192
  • gemma2.embedding_length
    2304
  • gemma2.feed_forward_length
    9216
  • gemma2.final_logit_softcapping
    30
  • general.architecture
    gemma2
  • general.basename
    gemma-2
  • general.file_type
    17
  • general.finetune
    it
  • general.name
    Gemma 2 2b It
  • general.organization
    Unsloth
  • general.quantization_version
    2
  • general.size_label
    2B
  • general.type
    model
  • tokenizer.ggml.add_bos_token
    true
  • tokenizer.ggml.add_eos_token
    false
  • tokenizer.ggml.add_space_prefix
    false
  • tokenizer.ggml.bos_token_id
    2
  • tokenizer.ggml.eos_token_id
    1
  • tokenizer.ggml.model
    llama
  • tokenizer.ggml.padding_token_id
    0
  • tokenizer.ggml.pre
    default
  • tokenizer.ggml.scores
    [-1000, -1000, -1000, -1000, -1000, ...]
  • tokenizer.ggml.token_type
    [3, 3, 3, 3, 3, ...]
  • tokenizer.ggml.tokens
    [<pad>, <eos>, <bos>, <unk>, <mask>, ...]
  • tokenizer.ggml.unknown_token_id
    3
    • Tensor
  • Name
    Type
    Shape
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    Q5_K
    [2048, 2304]
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    Q5_K
    [2304, 2048]
  • blk.0.attn_v.weight
    Q6_K
    [2304, 1024]
  • blk.0.ffn_down.weight
    Q6_K
    [9216, 2304]
  • blk.0.ffn_gate.weight
    Q5_K
    [2304, 9216]
  • blk.0.ffn_norm.weight
    F32
    [2304]
  • blk.0.ffn_up.weight
    Q5_K
    [2304, 9216]
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    F32
    [2304]
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    F32
    [2304]
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    Q5_K
    [2304, 1024]
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    F32
    [2304]
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    Q5_K
    [2048, 2304]
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    Q5_K
    [2304, 2048]
  • blk.1.attn_v.weight
    Q6_K
    [2304, 1024]
  • blk.1.ffn_down.weight
    Q6_K
    [9216, 2304]
  • blk.1.ffn_gate.weight
    Q5_K
    [2304, 9216]
  • blk.1.ffn_norm.weight
    F32
    [2304]
  • blk.1.ffn_up.weight
    Q5_K
    [2304, 9216]
  • blk.1.post_attention_norm.weight
    F32
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  • blk.1.post_ffw_norm.weight
    F32
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    Q5_K
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    F32
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    Q5_K
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    Q5_K
    [2304, 2048]
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    Q5_K
    [2304, 1024]
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    Q5_K
    [9216, 2304]
  • blk.2.ffn_gate.weight
    Q5_K
    [2304, 9216]
  • blk.2.ffn_norm.weight
    F32
    [2304]
  • blk.2.ffn_up.weight
    Q5_K
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    F32
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    F32
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    Q5_K
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    Q6_K
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    Q5_K
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  • blk.3.ffn_norm.weight
    F32
    [2304]
  • blk.3.ffn_up.weight
    Q5_K
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    F32
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  • blk.3.post_ffw_norm.weight
    F32
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    Q5_K
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    F32
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    Q5_K
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    Q5_K
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    Q5_K
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    Q5_K
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    Q5_K
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    F32
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    Q5_K
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    F32
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    F32
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    Q5_K
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    Q5_K
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    F32
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    Q5_K
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    F32
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