flan-t5-large-grammar-synthesis-gguf
107
2
license:apache-2.0
by
pszemraj
Language Model
OTHER
New
107 downloads
Early-stage
Edge AI:
Mobile
Laptop
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Unknown
Mobile
Laptop
Server
Quick Summary
AI model with specialized capabilities.
Training Data Analysis
🔵 Good (6.0/10)
Researched training datasets used by flan-t5-large-grammar-synthesis-gguf with quality assessment
Specialized For
general
multilingual
Training Datasets (1)
c4
🔵 6/10
general
multilingual
Key Strengths
- •Scale and Accessibility: 750GB of publicly available, filtered text
- •Systematic Filtering: Documented heuristics enable reproducibility
- •Language Diversity: Despite English-only, captures diverse writing styles
Considerations
- •English-Only: Limits multilingual applications
- •Filtering Limitations: Offensive content and low-quality text remain despite filtering
Explore our comprehensive training dataset analysis
View All DatasetsCode Examples
text
system_info: n_threads = 4 / 8 | AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 |
sampling:
repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
top_k = 40, tfs_z = 1.000, top_p = 0.950, min_p = 0.050, typical_p = 1.000, temp = 0.000
mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampling order:
CFG -> Penalties -> top_k -> tfs_z -> typical_p -> top_p -> min_p -> temperature
generate: n_ctx = 8192, n_batch = 2048, n_predict = -1, n_keep = 0
The car broke down so they had to take a ride to school. [end of text]
llama_print_timings: load time = 782.21 ms
llama_print_timings: sample time = 0.23 ms / 16 runs ( 0.01 ms per token, 68376.07 tokens per second)
llama_print_timings: prompt eval time = 85.08 ms / 19 tokens ( 4.48 ms per token, 223.33 tokens per second)
llama_print_timings: eval time = 341.74 ms / 15 runs ( 22.78 ms per token, 43.89 tokens per second)
llama_print_timings: total time = 456.56 ms / 34 tokens
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